Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-14T13:01:09.886963Z
Paper Citation Record · LEDGER
As of 15 August 2026, this Paper Citation Record lists 100 of 233 outbound references and 0 inbound Pith citation observations for arXiv:1908.07656.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-14T13:01:09.886963Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
100 of 233 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 9802fe7e-e35a-4ddb-82d6-aeb0ff5f0e71 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Driver inattention monitoring system for intelligent vehicles: A review,
Reference 1
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Observation e13739e9-5465-4847-9554-67e12ec63dff · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Video-based lane estimation and tracking for driver assistance: Survey, system, and evaluation,
Reference 2
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Observation 335e3c92-4dee-4a41-8f12-a7a801dd97e8 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems A Review of Computer Vision Techniques for the Analysis of Urban Traffic,
Reference 3
Source-reported events for the cited work
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Observation a7500238-0b10-4c1e-b714-b3ed6ad91f0d · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Looking at Humans in the Age of Self-Driving and Highly Automated Vehicles,
Reference 4
Source-reported events for the cited work
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Observation 1109e25c-6cf2-4150-9514-a54386c19326 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems End to End Learning for Self-Driving Cars
Reference 5
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c986f42e-207e-4716-8a4c-e7c594cc024f · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Lane-Change Detection Based on Vehicle-Trajectory Prediction,
Reference 6
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Observation e84d86f5-c469-4383-9569-e0a8e19a5708 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Single-pedestrian detection aided by two-pedestrian detection,
Reference 7
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Observation e5db191b-8100-49e6-96d8-420c1251b616 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Deep Architecture for Traffic Flow Prediction: Deep Belief Networks With Multitask Learning,
Reference 8
Source-reported events for the cited work
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Observation f72cae4d-5e06-44db-83d0-33cb29e58bba · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Capturing Car-Following Behaviors by Deep Learning,
Reference 9
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Observation 4249d6c4-cb8f-46c4-825b-b478b0e5ddf0 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Deep Learning for Reliable Mobile Edge Analytics in Intelligent Transportation Systems: An Overview,
Reference 10
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Observation 59c61f42-26b3-4574-b158-a6043c0eadd5 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Brain tumor segmentation with Deep Neural Networks,
Reference 11
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Observation f4c45c3b-762b-4d31-bdfc-500325342473 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Multimodal Neuroimaging Feature Learning for Multiclass Diagnosis of Alzheimer's Disease,
Reference 12
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Observation 827f7863-dde4-47e3-b0c6-118d0ab69d96 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Deep biomarkers of human aging: Application of deep neural networks to biomarker development,
Reference 13
Source-reported events for the cited work
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Observation 463c5b2d-66c1-44db-bf94-ef2a3b7f552b · outbound
Survey on Deep Neural Networks in Speech and Vision Systems An end-to-end computer vision pipeline for automated cardiac function assessment by echocardiography,
Reference 14
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Unavailable: canonical work link unavailable.
Observation 565e380b-daee-4c11-9108-c4f421219e14 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems A review of smart homes—Past, present, and future,
Reference 15
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Observation 4951d811-fc49-4712-a6f0-3092ce16a6a5 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Personal virtual assistant,
Reference 16
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Observation 8effee34-4ad6-4635-be05-790a4e0f6940 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Application of data mining techniques in customer relationship management: A literature review and classification,
Reference 17
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Observation c54934fb-e7d0-4e06-968c-06bed4a60cbd · outbound
Survey on Deep Neural Networks in Speech and Vision Systems A review on application of data mining techniques to combat natural disasters,
Reference 18
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Observation 28be8827-fa62-4b08-a8ef-00f990f63f45 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Vision based hand gesture recognition for human computer interaction: a survey,
Reference 19
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Observation ab10b8f9-204f-4adc-9875-c26cc8fede87 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Deeppose: Human pose estimation via deep neural networks,
Reference 20
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Observation 301a4bdd-fb8f-4fd4-837f-1414bf08ffcd · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Joint training of a convolutional network and a graphical model for human pose estimation,
Reference 21
Source-reported events for the cited work
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Observation 88c400a1-2f3c-49ea-a6ca-4598da99380c · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Safety and security in smart cities using artificial intelligence—A review,
Reference 22
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Observation 3164275e-c3a0-4939-94c2-e7122f84cec1 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Detecting depression severity from vocal prosody,
Reference 23
Source-reported events for the cited work
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Observation b98bc186-c8ee-4ce7-9eea-fa73127929ba · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Speech and prosody characteristics of adolescents and adults with high-functioning autism and Asperger syndrome,
Reference 24
Source-reported events for the cited work
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Observation 87f4e4ef-77bd-4df2-be33-b8d2a73d3761 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Survey on speech emotion recognition: Features, classification schemes, and databases,
Reference 25
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Observation 4db270f3-3de1-4607-95ce-7697892ff09c · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Evaluating deep learning architectures for Speech Emotion Recognition,
Reference 26
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Observation 1a7efe52-5a14-4af7-bffd-ebc9614ea687 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Deep learning for robust feature generation in audiovisual emotion recognition,
Reference 27
Source-reported events for the cited work
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Observation 647b53f5-ebaf-4431-8d07-eceb9ab49518 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems A fast learning algorithm for deep belief nets,
Reference 28
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Observation 3f555ffb-2710-4c3f-bad5-c376c509b950 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Learning multiple layers of representation,
Reference 29
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Observation 9717493d-9b56-472a-b111-66c52fa7c5cb · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence,
Reference 30
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Observation 406f3d56-6e94-4b20-977a-1da977106617 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Deep hierarchies in the primate visual cortex: What can we learn for computer vision?,
Reference 31
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Observation 9d6baccd-072a-492f-9179-ea913010af37 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Deep learning in neural networks: An overview,
Reference 32
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Observation 7131c250-b790-4778-a356-1c547b523a7a · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Imagenet classification with deep convolutional neural networks,
Reference 33
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Observation f4aac34f-6efa-4123-8813-dee70fbf2e7f · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion,
Reference 34
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Observation 5d3db918-db27-43b8-8990-d7f7cb14354b · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Generative adversarial nets,
Reference 35
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Observation bebd5e0f-1e50-4705-a1b7-d94c8ba72204 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Auto-Encoding Variational Bayes
Reference 36
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Observation a6ec1a85-2ede-4752-9260-960933c3b5e5 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Density estimation using Real NVP
Reference 37
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Observation 98d53d6c-b491-44ca-a39c-c4b46bb7734c · outbound
Survey on Deep Neural Networks in Speech and Vision Systems A Critical Review of Recurrent Neural Networks for Sequence Learning
Reference 38
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Observation 0b63cf57-7806-47df-b37b-241922040c13 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Attention is all you need,
Reference 39
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Observation 6854baa9-262b-421e-948c-93aad74e22fe · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Novel hierarchical Cellular Simultaneous Recurrent neural Network for object detection,
Reference 40
Source-reported events for the cited work
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Observation 9703dc47-7852-4c32-9190-4ee9cb2fcc09 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Restricted Boltzmann machines for collaborative filtering,
Reference 41
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Observation 10b34afc-3bfe-440b-9127-a587cc236667 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Deep boltzmann machines,
Reference 42
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Observation 18ce4847-0689-401e-99f6-70aca7fdcbe8 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Extracting deep bottleneck features using stacked auto-encoders,
Reference 43
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Unavailable: canonical work link unavailable.
Observation f42abfe2-e355-49a7-b038-c7ccd78440ef · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Extracting and composing robust features with denoising autoencoders,
Reference 44
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Unavailable: canonical work link unavailable.
Observation 81edcbb3-35e2-4335-a3b8-489f3ce5d2b5 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Learning hierarchical representations for face verification with convolutional deep belief networks,
Reference 45
Source-reported events for the cited work
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Observation bb3d104d-5db1-45da-9bbf-a34c0cf08ab3 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Investigation of deep boltzmann machines for phone recognition,
Reference 46
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Unavailable: canonical work link unavailable.
Observation 0c230678-7e24-4780-ac80-4fa256350fbc · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Random Deep Belief Networks for Recognizing Emotions from Speech Signals,
Reference 47
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Unavailable: canonical work link unavailable.
Observation 98c97ae5-df14-445a-9e73-37026f2bda07 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems A research of speech emotion recognition based on deep belief network and SVM,
Reference 48
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Observation b968b7c6-7da1-41d7-8119-a2f814ef4521 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations,
Reference 49
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Observation 9bb0f783-0f21-4b1b-88c6-6590654d45d8 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Attribute2image: Conditional image generation from visual attributes,
Reference 50
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Observation 4c18870d-f363-4e90-8b05-73f1ab7f9ea8 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems An uncertain future: Forecasting from static images using variational autoencoders,
Reference 51
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Observation 56ae4670-c184-4684-9ac8-16e755a53e74 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems A Hybrid Convolutional Variational Autoencoder for Text Generation
Reference 52
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Unavailable: canonical work link unavailable.
Observation e7f2dce6-2710-41a8-a792-6304c87001ce · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Expressive Speech Synthesis via Modeling Expressions with Variational Autoencoder
Reference 53
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Observation dc320539-c920-44b7-a109-57aa2996b697 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Generative Adversarial Text to Image Synthesis
Reference 54
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 29b2fc7b-0fe0-41c6-a9ad-3eaac2c2031b · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Photo-realistic single image super-resolution using a generative adversarial network,
Reference 55
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Observation 0cab5ea6-c721-4c3b-a308-b1d450a0f7a6 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Conditional Generative Adversarial Nets
Reference 56
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Observation bbcd27c7-99cf-4eb5-bd8a-9bf9b3dfdfe3 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems High-resolution image synthesis and semantic manipulation with conditional gans,
Reference 57
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Observation d5718e79-4e4a-440b-99fe-401cfea24ea8 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Adversarial Feature Learning
Reference 58
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Observation a5890251-a72e-4421-9450-f61869b2fe23 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Large scale adversarial representation learning,
Reference 59
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Observation a6eb334d-9741-4c1d-8b13-6f30ea70d02f · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Towards Principled Methods for Training Generative Adversarial Networks
Reference 60
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Unavailable: canonical work link unavailable.
Observation 8575c3e9-d130-4754-a87d-5633453b58d8 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems NIPS 2016 Tutorial: Generative Adversarial Networks
Reference 61
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Observation 500abceb-c6aa-4beb-afed-d73b8ac0818a · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Spectral Normalization for Generative Adversarial Networks
Reference 62
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Observation a9036aad-c42e-4806-94fb-7199bcc2ae7d · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Wasserstein generative adversarial networks,
Reference 63
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Observation c994c929-ad98-40f9-88d4-ec70dfdc02b7 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Improved training of wasserstein gans,
Reference 64
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Observation 79182df8-cf52-40f5-b9a4-bb583e18315b · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Least squares generative adversarial networks,
Reference 65
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Observation 9a79f556-6589-4605-bf88-4fc5de7da72d · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Generating Diverse High-Fidelity Images with VQ-VAE-2
Reference 66
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Observation dea243d5-3f79-4241-a8bd-419e5ae243a6 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems NICE: Non-linear Independent Components Estimation
Reference 67
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Observation b95d918b-9ed1-4163-98ab-491c81e456df · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Glow: Generative flow with invertible 1x1 convolutions,
Reference 68
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Observation 06f58d48-413d-402c-8233-44f33ec99c5b · outbound
Survey on Deep Neural Networks in Speech and Vision Systems WaveNet: A Generative Model for Raw Audio
Reference 69
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Observation 9714b967-d309-4423-8166-3f10e6571419 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Pixel Recurrent Neural Networks
Reference 70
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Observation 4d1b015d-be2b-4a83-9b78-eef6fe27badd · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Waveglow: A flow-based generative network for speech synthesis,
Reference 71
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Observation 6a817db0-8ef7-483e-bea8-1b9d860f057b · outbound
Survey on Deep Neural Networks in Speech and Vision Systems SEGAN: Speech Enhancement Generative Adversarial Network
Reference 72
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Observation 8ef72377-b71c-440f-8281-9b4d90a7b94a · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Speech Enhancement for Noise-Robust Speech Synthesis Using Wasserstein GAN}},
Reference 73
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Observation de37cad0-b38e-4af5-af52-67815a39a275 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
Reference 74
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Observation c620afa6-541e-4e5a-8189-cf7db4ba98e6 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems On the Properties of Neural Machine Translation: Encoder-Decoder Approaches
Reference 75
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Observation e2e1dc73-e61e-493a-8729-5d3634c58e3a · outbound
Survey on Deep Neural Networks in Speech and Vision Systems LSTM: A search space odyssey,
Reference 76
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Observation c565236c-97f2-475a-b08d-0ba358b7f87f · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Recurrent models of visual attention,
Reference 77
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Observation 165303af-f1c3-46cb-9eac-cadcd52d6e2b · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Learning to combine foveal glimpses with a third-order Boltzmann machine,
Reference 78
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Observation fa1bc016-cacc-4c93-a344-f45248c361b8 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems On Learning Where To Look
Reference 79
Source-reported events for the cited work
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Observation 6b5d8d92-cbb3-49cb-afcb-68a6ca2fba82 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Learning where to attend with deep architectures for image tracking,
Reference 80
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Observation 033eff53-4e1f-4af0-b159-196ff7d4c4be · outbound
Survey on Deep Neural Networks in Speech and Vision Systems DRAW: A Recurrent Neural Network For Image Generation
Reference 81
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Observation 77c4d083-049c-4154-87d2-18dae9787c4e · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Aligning Where to See and What to Tell: Image Captioning with Region-Based Attention and Scene-Specific Contexts,
Reference 82
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Observation 31aa1fdd-2095-4eea-a398-0cc198c395fa · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Generating Images from Captions with Attention
Reference 83
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Observation a45ec348-dc86-42ef-955f-c08dddb5ba1f · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Neural Turing Machines
Reference 84
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Observation e2b12437-d4e7-43f0-912a-907fb2f020bc · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Effective Approaches to Attention-based Neural Machine Translation
Reference 85
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Observation e19fbff3-82e8-4bc5-a43c-a000878bc251 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Listen, attend and spell: A neural network for large vocabulary conversational speech recognition,
Reference 86
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Observation 02618946-b16a-4dc0-bcca-59b3fbb0f9a3 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Skeleton-based action recognition using spatio-temporal LSTM network with trust gates,
Reference 87
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Observation 2a771925-8704-44ce-ba07-701759d77e02 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Self-Attention Generative Adversarial Networks
Reference 88
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Observation e6b92fbd-bdf7-4c26-9741-d3292038e5ca · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Neural Architecture Search with Reinforcement Learning
Reference 89
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Observation 391ea093-95bc-44d6-a1f0-265642c2c07e · outbound
Survey on Deep Neural Networks in Speech and Vision Systems DARTS: Differentiable Architecture Search
Reference 90
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Observation 56bba1c7-faf8-44b1-b83a-9966221dfa55 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Progressive neural architecture search,
Reference 91
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Observation b8331225-fd2a-4791-9e12-a7972010132e · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Learning hierarchical features for scene labeling,
Reference 92
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Observation aec87521-37eb-4fb7-9f73-0accffae8363 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Going deeper with convolutions,
Reference 93
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Observation 2c737217-3d2b-4c75-8deb-46f0547af6d4 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Imagenet large scale visual recognition challenge,
Reference 94
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Observation 1886ac6a-668f-4324-9636-d384629ebd32 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Very Deep Convolutional Networks for Large-Scale Image Recognition
Reference 95
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Observation ac9c22a0-d85a-4451-b3fd-915fe0c5fd21 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Visualizing and understanding convolutional networks,
Reference 96
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Observation b2b01d53-6e2e-4d7a-8940-85fade305c65 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Wider or Deeper: Revisiting the ResNet Model for Visual Recognition
Reference 97
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Observation 1dd5cb84-eae1-4d0f-ae2d-ddcaaa62127d · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Delving deep into rectifiers: Surpassing human-level performance on imagenet classification,
Reference 98
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Observation bf00056b-1b0d-47a4-8240-1e5286212507 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Densely connected convolutional networks,
Reference 99
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Observation 71464a5a-b82b-46f9-b4fa-80b85e596a41 · outbound
Survey on Deep Neural Networks in Speech and Vision Systems Squeeze-and-excitation networks,
Reference 100
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No inbound Pith citation observations are available.