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Paper Citation Record · LEDGER

Efficient Deep Neural Networks

As of 22 August 2026, this Paper Citation Record lists 100 of 181 outbound references and 0 inbound Pith citation observations for arXiv:1908.08926.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1908.08926 v1

Coverage vector

measured 100 of 181 reference resolution

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measured 100 of 100 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

100 of 181 outbound references displayed

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External citation measurements

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Outbound references

Observation 2ec01566-f5d1-42c4-a2f4-8b3ccc48bf66 · outbound

This paper cites The Vapnik-Chervonenkis dimension: Information versus com- plexity in learning.

Efficient Deep Neural Networks The Vapnik-Chervonenkis dimension: Information versus com- plexity in learning

Reference 1

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Observation 2711d48e-0bb0-4dfb-9df3-f4d2a226a710 · outbound

This paper cites Efficient Interactive Annotation of Segmentation Datasets with Polygon-RNN++.

Efficient Deep Neural Networks Efficient Interactive Annotation of Segmentation Datasets with Polygon-RNN++

Reference 2

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Observation dfdac729-99f2-4243-b36c-d24625ab6d94 · outbound

This paper cites Shallow Networks for High-Accuracy Road Object-Detection.

Efficient Deep Neural Networks Shallow Networks for High-Accuracy Road Object-Detection

Reference 3

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Observation 604d3f5b-ede4-4ab7-9f78-49dc714c6e78 · outbound

This paper cites Label Refinery: Improving ImageNet Classification through Label Progression.

Efficient Deep Neural Networks Label Refinery: Improving ImageNet Classification through Label Progression

Reference 4

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Observation 69a3cff5-9b51-4da0-8792-ecef25b0932c · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

Efficient Deep Neural Networks Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 5

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Observation 6112699b-341a-4a69-a3fe-4a2c344b5141 · outbound

This paper cites FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks.

Efficient Deep Neural Networks FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks

Reference 6

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This paper cites Unsupervised pixel-level domain adaptation with gen- erative adversarial networks.

Efficient Deep Neural Networks Unsupervised pixel-level domain adaptation with gen- erative adversarial networks

Reference 7

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Observation b72991b5-d75c-4924-9368-eb8062ef3ea6 · outbound

This paper cites A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection.

Efficient Deep Neural Networks A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection

Reference 8

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Observation 5de02892-1a12-4bfd-bfdd-331a281bec2c · outbound

This paper cites Fast LIDAR-based Road Detection Using Fully Convolutional Neural Networks.

Efficient Deep Neural Networks Fast LIDAR-based Road Detection Using Fully Convolutional Neural Networks

Reference 9

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Observation c3839e3b-a5dc-4747-9b23-73a950ed4a51 · outbound

This paper cites Annotating object instances with a polygon-rnn.

Efficient Deep Neural Networks Annotating object instances with a polygon-rnn

Reference 10

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This paper cites DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs.

Efficient Deep Neural Networks DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

Reference 11

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Observation c2ac8184-7c16-4556-af0f-9b905b02855f · outbound

This paper cites All You Need is a Few Shifts: Designing Efficient Convolutional Neural Networks for Image Classification.

Efficient Deep Neural Networks All You Need is a Few Shifts: Designing Efficient Convolutional Neural Networks for Image Classification

Reference 12

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Observation 751a8dd8-1c7f-4a85-bbd8-96d49e2f81fa · outbound

This paper cites Multi-View 3D Object Detection Network for Autonomous Driving.

Efficient Deep Neural Networks Multi-View 3D Object Detection Network for Autonomous Driving

Reference 13

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Observation cef7af58-330c-4e7a-8e0a-2d4b483eaf1f · outbound

This paper cites DetNAS: Backbone Search for Object Detection.

Efficient Deep Neural Networks DetNAS: Backbone Search for Object Detection

Reference 14

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Observation c6557833-1db6-4921-85ee-9275cb216349 · outbound

This paper cites cuDNN: Efficient Primitives for Deep Learning.

Efficient Deep Neural Networks cuDNN: Efficient Primitives for Deep Learning

Reference 15

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Observation d51e9ec8-f881-4df0-b22e-08e2c21ca1f3 · outbound

This paper cites PACT: Parameterized Clipping Activation for Quantized Neural Networks.

Efficient Deep Neural Networks PACT: Parameterized Clipping Activation for Quantized Neural Networks

Reference 16

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Observation 179e128a-3d4b-44aa-85f8-1ca68d9d5f49 · outbound

This paper cites Xception: Deep Learning with Depthwise Separable Convolutions.

Efficient Deep Neural Networks Xception: Deep Learning with Depthwise Separable Convolutions

Reference 17

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Observation fd9bc8c2-2140-4176-8fb9-6e956c4da554 · outbound

This paper cites Visual Wake Words Dataset.

Efficient Deep Neural Networks Visual Wake Words Dataset

Reference 18

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Observation 9d4e72c8-0a56-4bf1-8815-eebec2c0ccb8 · outbound

This paper cites Domain Adaptation for Visual Applications: A Comprehensive Survey.

Efficient Deep Neural Networks Domain Adaptation for Visual Applications: A Comprehensive Survey

Reference 19

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Observation 6d0d0ac1-d69e-49d9-aeda-d405680392e0 · outbound

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Efficient Deep Neural Networks Histograms of Oriented Gradients for Human Detec- tion

Reference 20

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Observation 49b7c034-8b23-4410-82c5-aad3bc04d7df · outbound

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Efficient Deep Neural Networks Imagenet: A large-scale hierarchical image database

Reference 21

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Observation ae365b72-0a84-46af-82ae-9dbff7f0cef2 · outbound

This paper cites HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precision.

Efficient Deep Neural Networks HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precision

Reference 22

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Efficient Deep Neural Networks CARLA: An Open Urban Driving Simulator

Reference 23

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Efficient Deep Neural Networks On the segmentation of 3D LIDAR point clouds

Reference 24

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Efficient Deep Neural Networks On the segmentation of 3D LIDAR point clouds

Reference 25

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Efficient Deep Neural Networks Dutta, A

Reference 26

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This paper cites A Density-based Algorithm for Discovering Clusters a Density- based Algorithm for Discovering Clusters in Large Spatial Databases with Noise.

Efficient Deep Neural Networks A Density-based Algorithm for Discovering Clusters a Density- based Algorithm for Discovering Clusters in Large Spatial Databases with Noise

Reference 27

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Observation 03f52c2c-c976-4f05-85d8-0a1e43a21038 · outbound

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Efficient Deep Neural Networks The Pascal Visual Object Classes (VOC) Challenge

Reference 28

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Efficient Deep Neural Networks Object detection with discriminatively trained part- based models

Reference 29

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Efficient Deep Neural Networks Scenic: a language for scenario specification and scene gen- eration

Reference 30

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Efficient Deep Neural Networks Domain-adversarial training of neural networks

Reference 31

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Efficient Deep Neural Networks A Neural Algorithm of Artistic Style

Reference 32

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Observation 28dc2a53-05c5-43ca-a1be-7f7f2d9c24fd · outbound

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Efficient Deep Neural Networks Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 33

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Efficient Deep Neural Networks Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 34

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Efficient Deep Neural Networks Deep reconstruction-classification networks for unsuper- vised domain adaptation

Reference 35

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Efficient Deep Neural Networks Domain generalization for object recognition with multi- task autoencoders

Reference 36

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Observation cadc9ca1-3c55-4ca5-bfd4-b215e182d21f · outbound

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Efficient Deep Neural Networks SqueezeNext: Hardware-Aware Neural Network Design

Reference 37

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Observation c8cf4cae-15ec-4b38-ace6-e15536204729 · outbound

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Efficient Deep Neural Networks Fast R-CNN

Reference 38

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Observation 49011878-abce-4509-b061-55935cd5204c · outbound

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Efficient Deep Neural Networks Deformable Part Models are Convolutional Neural Networks

Reference 39

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Efficient Deep Neural Networks Rich feature hierarchies for accurate object detection and semantic segmentation

Reference 40

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Observation b6956c08-3538-4ba1-a461-64516ecac71f · outbound

This paper cites Supplementary Material: Rich feature hierarchies for accurate object detection and semantic segmentation.

Efficient Deep Neural Networks Supplementary Material: Rich feature hierarchies for accurate object detection and semantic segmentation

Reference 41

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Observation a487f029-b190-4ca6-8e72-7351091ed32a · outbound

This paper cites Software-Hardware Codesign for Efficient Neural Network Ac- celeration.

Efficient Deep Neural Networks Software-Hardware Codesign for Efficient Neural Network Ac- celeration

Reference 42

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Observation f956af2d-2d4e-4a01-a31b-9848fa13cc7c · outbound

This paper cites Ms-celeb-1m: Challenge of recognizing one million celebrities in the real world.

Efficient Deep Neural Networks Ms-celeb-1m: Challenge of recognizing one million celebrities in the real world

Reference 43

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Observation 3e5a560c-1d32-4f67-91d7-abb5efb40731 · outbound

This paper cites Single Path One-Shot Neural Architecture Search with Uniform Sampling.

Efficient Deep Neural Networks Single Path One-Shot Neural Architecture Search with Uniform Sampling

Reference 44

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Observation 56933147-b87c-487c-8ea7-8c7d88c916a2 · outbound

This paper cites The unreasonable effectiveness of data.

Efficient Deep Neural Networks The unreasonable effectiveness of data

Reference 45

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Observation e874090a-36f6-4753-8d3d-29db09332d27 · outbound

This paper cites Deep Compression: Compressing DNNs with Pruning, Trained Quantization and Huffman Coding.

Efficient Deep Neural Networks Deep Compression: Compressing DNNs with Pruning, Trained Quantization and Huffman Coding

Reference 46

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Observation 197d12ff-dc88-4194-9b80-895993347ea1 · outbound

This paper cites Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding.

Efficient Deep Neural Networks Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

Reference 47

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source=pdf_text observed=2026-08-14T12:19:53.458539Z digest=sha256:655a5994d2643fa6d90ec482cb488e5678f87c1369f28ee08db4396799d476f8

Observation 36396b45-d17a-402b-9ed8-d682298078f5 · outbound

This paper cites Achieving Human Parity on Automatic Chinese to English News Translation.

Efficient Deep Neural Networks Achieving Human Parity on Automatic Chinese to English News Translation

Reference 48

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source=pdf_text observed=2026-08-14T12:19:53.463873Z digest=sha256:75b627326aeab6e16daaef540cfdbbd00129dbc326e5b7705ec75576a0922cbe

Observation af56d365-1384-438e-8345-ff44724bf29b · outbound

This paper cites Deep Residual Learning for Image Recognition.

Efficient Deep Neural Networks Deep Residual Learning for Image Recognition

Reference 49

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source=pdf_text observed=2026-08-14T12:19:53.468969Z digest=sha256:c5691357b296ddb6e18f759e86941027475c828e6757a5673b96c57182f4b9fb

Observation 71cda0b5-7f68-4dd7-bb50-8566dce0d84c · outbound

This paper cites Deep residual learning for image recognition.

Efficient Deep Neural Networks Deep residual learning for image recognition

Reference 50

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Observation e8787b2d-3823-4a1d-aea1-609df6288973 · outbound

This paper cites Identity mappings in deep residual networks.

Efficient Deep Neural Networks Identity mappings in deep residual networks

Reference 51

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source=pdf_text observed=2026-08-14T12:19:53.480147Z digest=sha256:c6887855fd7992ae7860aec22ec38ddeaf39670baca01c6168a01781d8ef3e5c

Observation f85c0c5e-51c0-4125-8b73-f4c89b9e686e · outbound

This paper cites Mask r-cnn.

Efficient Deep Neural Networks Mask r-cnn

Reference 52

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source=pdf_text observed=2026-08-14T12:19:53.484941Z digest=sha256:41c049a14eace077c16fc24a3c5d5e623bc768afdfec089729f4196757d807e3

Observation 869450c0-1917-4c25-a439-df51a21c274b · outbound

This paper cites Addressnet: Shift-based primitives for efficient convolutional neural networks.

Efficient Deep Neural Networks Addressnet: Shift-based primitives for efficient convolutional neural networks

Reference 53

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source=pdf_text observed=2026-08-14T12:19:53.489759Z digest=sha256:cdcf5defb9782ae7f6e6831806e485dddf8fad6624f992ac4a82c1acef8519cf

Observation de81de27-6881-4180-b522-6f5b6492c093 · outbound

This paper cites AMC: AutoML for Model Compression and Acceleration on Mobile Devices.

Efficient Deep Neural Networks AMC: AutoML for Model Compression and Acceleration on Mobile Devices

Reference 54

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source=pdf_text observed=2026-08-14T12:19:53.494547Z digest=sha256:4922fb73e42ea8230269b31f83c5b87773b31693456576c7500f7364dd44567a

Observation 60e528f8-c534-477c-9b30-a5940d824db0 · outbound

This paper cites LIDAR-based 3D object perception.

Efficient Deep Neural Networks LIDAR-based 3D object perception

Reference 55

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source=pdf_text observed=2026-08-14T12:19:53.499752Z digest=sha256:1074f8f235341b75e559af6d2757e6c83053eb9ab69859d914102a0578e6cd19

Observation 6be9eea1-96af-4da5-b3e9-bc1cf0e3601b · outbound

This paper cites CyCADA: Cycle-Consistent Adversarial Domain Adaptation.

Efficient Deep Neural Networks CyCADA: Cycle-Consistent Adversarial Domain Adaptation

Reference 56

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source=pdf_text observed=2026-08-14T12:19:53.504754Z digest=sha256:8ebe94c34fedb940831531bb40476a0371f9a8abafe3874f662edf2eca2498d7

Observation c53cac01-349d-49b1-82b1-fc038ff28885 · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

Efficient Deep Neural Networks MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 58

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source=pdf_text observed=2026-08-14T12:19:53.516223Z digest=sha256:3f67ef126b69f5128471b46a45dc52f479b37bf5058bd5a3f6cd237fbffacce8

Observation 611672a4-baa9-43a5-b5dc-2a6af153f9c1 · outbound

This paper cites Searching for MobileNetV3.

Efficient Deep Neural Networks Searching for MobileNetV3

Reference 59

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source=pdf_text observed=2026-08-14T12:19:53.521579Z digest=sha256:73de1e39740c475735eb98c77f349780c2bf16ffd74e4d79cbac34bbe7511dd3

Observation 0a7b0bdb-94bb-42de-bea5-e00597206775 · outbound

This paper cites Squeeze-and-excitation networks.

Efficient Deep Neural Networks Squeeze-and-excitation networks

Reference 60

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source=pdf_text observed=2026-08-14T12:19:53.534338Z digest=sha256:782760e3b4695812e7bbfc8bc958f0ed6281f97c4e472c304209524b3c4eb37e

Observation 87db7b75-88b3-4d4d-933a-0f76acce4d36 · outbound

This paper cites Densely Connected Convolutional Networks.

Efficient Deep Neural Networks Densely Connected Convolutional Networks

Reference 61

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source=pdf_text observed=2026-08-14T12:19:53.539688Z digest=sha256:b8223ff60cd8594ba36b75a6f7f3ad4fc3c3b5e73c36ee9df352f0cbede8fc39

Observation 5e6225bd-009f-48de-be2b-610a760b0090 · outbound

This paper cites Rethinking the inception architecture for computer vision.

Efficient Deep Neural Networks Rethinking the inception architecture for computer vision

Reference 62

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source=pdf_text observed=2026-08-14T12:19:53.544490Z digest=sha256:30589ac3697f2c7ea4c7172a8a7196b85477fb2702e6aa6977bd276effe8d244

Observation 7f3d99e3-b8fe-4eec-94ae-4487644ce94d · outbound

This paper cites The apolloscape dataset for autonomous driving.

Efficient Deep Neural Networks The apolloscape dataset for autonomous driving

Reference 63

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source=pdf_text observed=2026-08-14T12:19:53.550345Z digest=sha256:b1b8d9828cbdec2c29dd7943ac44192fe5928616385f5bb9236f11479b620f4c

Observation 948bc508-43f5-40b8-90f6-364c4d08aaff · outbound

This paper cites DenseNet: Implementing Efficient ConvNet Descriptor Pyramids.

Efficient Deep Neural Networks DenseNet: Implementing Efficient ConvNet Descriptor Pyramids

Reference 64

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source=pdf_text observed=2026-08-14T12:19:53.555866Z digest=sha256:42d96cd3bd3d06910bbae6aae8de6fd6e428dbe5534cec65f11a1c29bb123291

Observation ec95d0c1-feff-4cb6-9c0b-559a27ccfc31 · outbound

This paper cites SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size.

Efficient Deep Neural Networks SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size

Reference 66

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source=pdf_text observed=2026-08-14T12:19:53.566440Z digest=sha256:7d5d6024f311e4bec771f6881ea04c5a6e9b4654784b63e691f71c4bf25603ed

Observation 518bfc4b-f1b6-497a-ad54-d5bd35134f9e · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal covariate shift.

Efficient Deep Neural Networks Batch normalization: Accelerating deep network training by reducing internal covariate shift

Reference 67

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source=pdf_text observed=2026-08-14T12:19:53.571543Z digest=sha256:e08746bc1a38f77748f92de5db0936a88b30192964de94e0b01afb42fb4d0ba9

Observation add08769-768e-4c9a-9dde-878b670bca6a · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

Efficient Deep Neural Networks Categorical Reparameterization with Gumbel-Softmax

Reference 68

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source=pdf_text observed=2026-08-14T12:19:53.576669Z digest=sha256:1f0438d83a548c72f0d856874161682479867d18225187c3528c14b7118e3fe4

Observation 7ba52d64-782a-4b9c-9644-2159f65e8f5c · outbound

This paper cites Caffe: Convolutional Architecture for Fast Feature Embedding.

Efficient Deep Neural Networks Caffe: Convolutional Architecture for Fast Feature Embedding

Reference 69

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source=pdf_text observed=2026-08-14T12:19:53.581656Z digest=sha256:e89cec3d6bf7a2f982bff639bf4def1707ee59644387ad1f946d753d581f1c6a

Observation 41cde180-6434-441f-bb4c-75699c579f73 · outbound

This paper cites Accelerating low bit-width convolutional neural networks with em- bedded FPGA.

Efficient Deep Neural Networks Accelerating low bit-width convolutional neural networks with em- bedded FPGA

Reference 70

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source=pdf_text observed=2026-08-14T12:19:53.586287Z digest=sha256:d58585e503cdbbf3427d98d278e88593ba873a2d3f3c1b80688e59cc5d9447ef

Observation 50715c44-eb90-4abf-af38-9664ec17ceed · outbound

This paper cites Perceptual Losses for Real-Time Style Transfer and Super-Resolution.

Efficient Deep Neural Networks Perceptual Losses for Real-Time Style Transfer and Super-Resolution

Reference 71

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source=pdf_text observed=2026-08-14T12:19:53.591332Z digest=sha256:e0e216af50c553735b82c7c9e084fcdd193b2c9f81d1a8dba282907db8244129

Observation e9824cd3-55c1-4512-88e1-6fab87875955 · outbound

This paper cites Driving in the Matrix: Can Virtual Worlds Replace Human-Generated Annotations for Real World Tasks?.

Efficient Deep Neural Networks Driving in the Matrix: Can Virtual Worlds Replace Human-Generated Annotations for Real World Tasks?

Reference 72

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source=pdf_text observed=2026-08-14T12:19:53.596401Z digest=sha256:cad2b607689077b9b65b488c6e062fb763f8d155c3ec8acfa3b155071d4a0235

Observation 6b07934d-41bb-46c3-a267-7869b6c6668e · outbound

This paper cites Driving in the matrix: Can virtual worlds replace human-generated annotations for real world tasks?.

Efficient Deep Neural Networks Driving in the matrix: Can virtual worlds replace human-generated annotations for real world tasks?

Reference 73

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source=pdf_text observed=2026-08-14T12:19:53.602134Z digest=sha256:e5f70d7ee0478adeb89faa14e20dfde48c0b5398f750611a0fa458677108f2d5

Observation 9b1ff8c6-6f8e-45ea-84b3-b9f48d8b4268 · outbound

This paper cites Local Binary Convolutional Neural Networks.

Efficient Deep Neural Networks Local Binary Convolutional Neural Networks

Reference 74

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source=pdf_text observed=2026-08-14T12:19:53.606975Z digest=sha256:a5e066c175f4cc09850cf9c9a56caa73d0b35d5102f01affb87beb02692f8e67

Observation 8d4a21af-f7f7-49cc-8961-b5b9ca6a6223 · outbound

This paper cites Learning to Quantize Deep Networks by Optimizing Quantization Intervals with Task Loss.

Efficient Deep Neural Networks Learning to Quantize Deep Networks by Optimizing Quantization Intervals with Task Loss

Reference 75

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source=pdf_text observed=2026-08-14T12:19:53.611892Z digest=sha256:29e310ec658c6f27656616d4a8c012309ebf0daefa5dfb8973be575f1235e0b3

Observation b85881c2-0895-4820-b4f5-3a9d63340106 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Efficient Deep Neural Networks Adam: A Method for Stochastic Optimization

Reference 76

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source=pdf_text observed=2026-08-14T12:19:53.616787Z digest=sha256:4ba5e0a813281a58a1b074f17bc6a484bdbb03e30e0d453a252a9b08b53f0b73

Observation 862dd1f3-f6f7-4873-94ae-4857ce5a4be2 · outbound

This paper cites Free supervision from video games.

Efficient Deep Neural Networks Free supervision from video games

Reference 77

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source=pdf_text observed=2026-08-14T12:19:53.621277Z digest=sha256:cf12c8fb8ce6939aca70d8e925b404cea9fd4edf7149253467ca3d5f91582d50

Observation 1e1131b0-c1f1-4a60-a815-f5673577e129 · outbound

This paper cites Efficient inference in fully connected crfs with gaussian edge potentials.

Efficient Deep Neural Networks Efficient inference in fully connected crfs with gaussian edge potentials

Reference 78

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source=pdf_text observed=2026-08-14T12:19:53.625762Z digest=sha256:af35cb2db76c40a52c608bdd42ef2ae542f56ba923aafc32b5ede550440281dd

Observation 232a1255-efff-4487-ae38-81bbf3e2d003 · outbound

This paper cites Learning multiple layers of features from tiny images.

Efficient Deep Neural Networks Learning multiple layers of features from tiny images

Reference 79

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source=pdf_text observed=2026-08-14T12:19:53.632080Z digest=sha256:962436ff5d8924809d020cb1263e52b7a4eb4b26895658ca67f34218110f98de

Observation b45b4d12-de28-4531-959c-25006dcbb4ba · outbound

This paper cites ImageNet Classification with Deep Convolutional Neural Networks.

Efficient Deep Neural Networks ImageNet Classification with Deep Convolutional Neural Networks

Reference 80

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source=pdf_text observed=2026-08-14T12:19:53.637204Z digest=sha256:768287d397e98845416daa04cb9ac861eb9d6bd4b3951f685266d7c60a89ad68

Observation 10b897b6-a939-490f-9397-301cbf6eb469 · outbound

This paper cites Imagenet classification with deep convolutional neural networks.

Efficient Deep Neural Networks Imagenet classification with deep convolutional neural networks

Reference 81

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source=pdf_text observed=2026-08-14T12:19:53.642831Z digest=sha256:56ef3f3b1da79e1b988e4455217f8ea73204cf092540098cf4ad835784dd912a

Observation 0667944b-87ec-4236-ac27-c5817e81fa5b · outbound

This paper cites Maestro: A Memory-on-Logic Architecture for Coordinated Parallel Use of Many Systolic Arrays.

Efficient Deep Neural Networks Maestro: A Memory-on-Logic Architecture for Coordinated Parallel Use of Many Systolic Arrays

Reference 82

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source=pdf_text observed=2026-08-14T12:19:53.650101Z digest=sha256:3dcc5bcd72617638654397dc785505f75aae43fcffaaa8a99ba6bfe39ad2b975

Observation 458fae54-bdb7-4c9b-a774-a9e0225ec4f7 · outbound

This paper cites Research methods in human-computer interaction.

Efficient Deep Neural Networks Research methods in human-computer interaction

Reference 83

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source=pdf_text observed=2026-08-14T12:19:53.655359Z digest=sha256:d186706909d2c718fd7726e09488ef08dd0d5ffbf03326a2e51a225bac790bb9

Observation 95e64fd7-1bda-4a2d-b620-9e31f071811e · outbound

This paper cites Extremely Low Bit Neural Network: Squeeze the Last Bit Out with ADMM.

Efficient Deep Neural Networks Extremely Low Bit Neural Network: Squeeze the Last Bit Out with ADMM

Reference 84

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Observation 5bd5b1f6-16ac-45c3-8d0b-2ce30f5250af · outbound

This paper cites Vehicle Detection from 3D Lidar Using Fully Convolutional Network.

Efficient Deep Neural Networks Vehicle Detection from 3D Lidar Using Fully Convolutional Network

Reference 85

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Observation 2917963e-4648-4b3c-a24e-6844920888ab · outbound

This paper cites Adaptive Batch Normalization for practical domain adaptation.

Efficient Deep Neural Networks Adaptive Batch Normalization for practical domain adaptation

Reference 86

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Observation 0d1e2cac-9565-4188-972d-d917e62a8751 · outbound

This paper cites Tiny-DSOD: Lightweight Object Detection for Resource-Restricted Usages.

Efficient Deep Neural Networks Tiny-DSOD: Lightweight Object Detection for Resource-Restricted Usages

Reference 87

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Observation ea02eb2b-24ea-44d5-a70f-bdb15c37770d · outbound

This paper cites FP-BNN: Binarized neural network on FPGA.

Efficient Deep Neural Networks FP-BNN: Binarized neural network on FPGA

Reference 88

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Observation 7a6b8673-7b60-433b-996f-40bc427bd64c · outbound

This paper cites TSM: Temporal Shift Module for Efficient Video Understanding.

Efficient Deep Neural Networks TSM: Temporal Shift Module for Efficient Video Understanding

Reference 89

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source=pdf_text observed=2026-08-14T12:19:53.694910Z digest=sha256:2bbca42a9a087be456732d64cc463b9d2a53ac69cf3bda6d89d9615289481468

Observation cb110077-be60-4f87-b9fc-326559bffcce · outbound

This paper cites Focal loss for dense object detection.

Efficient Deep Neural Networks Focal loss for dense object detection

Reference 90

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Observation adbf9402-281a-47b9-8375-28b22d6c4407 · outbound

This paper cites Microsoft COCO: Common Objects in Context.

Efficient Deep Neural Networks Microsoft COCO: Common Objects in Context

Reference 91

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Observation b611cfb5-8452-4258-9f05-9c3e9835586d · outbound

This paper cites Progressive Neural Architecture Search.

Efficient Deep Neural Networks Progressive Neural Architecture Search

Reference 92

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Observation 1bc00182-e4f2-4565-bd0c-e91e64da5ebb · outbound

This paper cites DARTS: Differentiable Architecture Search.

Efficient Deep Neural Networks DARTS: Differentiable Architecture Search

Reference 93

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Observation 688992c3-8f30-4fe5-af6e-c2bc26876f3d · outbound

This paper cites Coupled generative adversarial networks.

Efficient Deep Neural Networks Coupled generative adversarial networks

Reference 94

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Observation 8646009a-4b4a-41cd-b549-0b1ee5106c5d · outbound

This paper cites Ssd: Single shot multibox detector.

Efficient Deep Neural Networks Ssd: Single shot multibox detector

Reference 95

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source=pdf_text observed=2026-08-14T12:19:53.741982Z digest=sha256:2cba51493897799ff2584b13114ce27558e91e216330288dcabb4f4d24c99700

Observation 9d35c388-f72b-4f4a-a71d-f832f2b56a6d · outbound

This paper cites MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning.

Efficient Deep Neural Networks MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning

Reference 96

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Observation 06c4b7cb-555e-4bdf-87b9-1219ad9058bb · outbound

This paper cites Fully Convolutional Networks for Semantic Segmentation.

Efficient Deep Neural Networks Fully Convolutional Networks for Semantic Segmentation

Reference 97

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source=pdf_text observed=2026-08-14T12:19:53.753905Z digest=sha256:8431addef19e09cb9876ae7d5c5f5bad5955b308f28c5683152352fb5891e035

Observation cb0c2b90-04a8-4f0e-b733-44496e412542 · outbound

This paper cites Learning transferable features with deep adaptation net- works.

Efficient Deep Neural Networks Learning transferable features with deep adaptation net- works

Reference 98

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Observation b22a9383-bee0-4baf-8463-67b09d4452c9 · outbound

This paper cites ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design.

Efficient Deep Neural Networks ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design

Reference 99

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Observation b6cebff1-c011-49d4-82dd-e5d4dc448534 · outbound

This paper cites The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables.

Efficient Deep Neural Networks The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables

Reference 100

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Observation 2367b1b8-4224-4def-b431-07b8bade5d47 · outbound

This paper cites TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems.

Efficient Deep Neural Networks TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems

Reference 101

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Observation 9657d810-31b2-4cb0-a563-a18cf7329c0d · outbound

This paper cites 3d convolutional neural networks for land- ing zone detection from lidar.

Efficient Deep Neural Networks 3d convolutional neural networks for land- ing zone detection from lidar

Reference 102

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Pith citing papers

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