Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition | Paper Citation Record

Observation eefb018e-e40b-4de1-9abb-d71de2e0893d · outbound

This paper cites A pid controller approach for stochastic optimization of deep networks.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition A pid controller approach for stochastic optimization of deep networks

Reference 1

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This paper cites Towards principled methods for training generative adversarial networks.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Towards principled methods for training generative adversarial networks

Reference 2

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This paper cites Wasserstein generative adversarial networks.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Wasserstein generative adversarial networks

Reference 3

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This paper cites Poof: Part-based one-vs.-one features for ﬁne-grained categorization, face veriﬁcation, and attribute estimation.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Poof: Part-based one-vs.-one features for ﬁne-grained categorization, face veriﬁcation, and attribute estimation

Reference 4

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This paper cites Describing people: A poselet-based approach to attribute classiﬁcation.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Describing people: A poselet-based approach to attribute classiﬁcation

Reference 5

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This paper cites Semi- Supervised Learning.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Semi- Supervised Learning

Reference 6

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This paper cites Chen and W.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Chen and W

Reference 7

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This paper cites Goodfellow, and Jonathon Shlens.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Goodfellow, and Jonathon Shlens

Reference 8

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Observation e7709ee8-c00c-4e63-accb-d0edde5e001b · outbound

This paper cites Semi-supervised multimodal deep learning for rgb-d object recognition.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Semi-supervised multimodal deep learning for rgb-d object recognition

Reference 9

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This paper cites Semi-supervised learning of facial attributes in video.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Semi-supervised learning of facial attributes in video

Reference 10

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This paper cites Semi-supervised sequence learning.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Semi-supervised sequence learning

Reference 11

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Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Unresolved cited work

Reference 12

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This paper cites Adversarial Feature Learning.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Adversarial Feature Learning

Reference 13

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This paper cites Training generative neural networks via maximum mean discrepancy optimization.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Training generative neural networks via maximum mean discrepancy optimization

Reference 14

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Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Unresolved cited work

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This paper cites Semi-Supervised Sparse Representation Based Classification for Face Recognition with Insufficient Labeled Samples.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Semi-Supervised Sparse Representation Based Classification for Face Recognition with Insufficient Labeled Samples

Reference 16

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This paper cites Generative adversarial nets.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Generative adversarial nets

Reference 17

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This paper cites NIPS 2016 Tutorial: Generative Adversarial Networks.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition NIPS 2016 Tutorial: Generative Adversarial Networks

Reference 18

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This paper cites A kernel two-sample test.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition A kernel two-sample test

Reference 19

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This paper cites Digital selection and analogue ampliﬁ- cation coexist in a cortex-inspired silicon circuit.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Digital selection and analogue ampliﬁ- cation coexist in a cortex-inspired silicon circuit

Reference 20

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This paper cites Deep residual learning for image recognition.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Deep residual learning for image recognition

Reference 21

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This paper cites Nlh: A blind pixel-level non-local method for real-world image denoising, 2019.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Nlh: A blind pixel-level non-local method for real-world image denoising, 2019

Reference 22

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This paper cites Hospedales, and Jakob Verbeek.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Hospedales, and Jakob Verbeek

Reference 23

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This paper cites Huang, Manu Ramesh, Tamara Berg, and Erik Learned-Miller.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Huang, Manu Ramesh, Tamara Berg, and Erik Learned-Miller

Reference 24

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This paper cites Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Reference 25

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This paper cites Semi-supervised learning with deep generative models.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Semi-supervised learning with deep generative models

Reference 26

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This paper cites Suspect identiﬁcation based on descriptive facial attributes.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Suspect identiﬁcation based on descriptive facial attributes

Reference 27

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

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Learning multiple layers of features from tiny images

Reference 28

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This paper cites Imagenet classiﬁcation with deep convolutional neural networks.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Imagenet classiﬁcation with deep convolutional neural networks

Reference 29

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This paper cites Facetracer: A search engine for large collections of images with faces.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Facetracer: A search engine for large collections of images with faces

Reference 30

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This paper cites Describable visual attributes for face veriﬁcation and image search.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Describable visual attributes for face veriﬁcation and image search

Reference 31

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This paper cites Attribute and simile classiﬁers for face veriﬁcation.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Attribute and simile classiﬁers for face veriﬁcation

Reference 32

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This paper cites Gradient-based learning applied to document recognition.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Gradient-based learning applied to document recognition

Reference 33

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This paper cites Mmd gan: Towards deeper understanding of moment matching network.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Mmd gan: Towards deeper understanding of moment matching network

Reference 34

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Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Unresolved cited work

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This paper cites A hybrid l1-l0 layer decomposition model for tone mapping.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition A hybrid l1-l0 layer decomposition model for tone mapping

Reference 36

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This paper cites Classiﬁcation and regression by randomforest.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Classiﬁcation and regression by randomforest

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Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Unresolved cited work

Reference 38

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This paper cites Liu and J.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Liu and J

Reference 39

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This paper cites Deep learning face attributes in the wild.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Deep learning face attributes in the wild

Reference 40

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This paper cites Auxiliary Deep Generative Models.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Auxiliary Deep Generative Models

Reference 41

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This paper cites Maas, Awni Y.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Maas, Awni Y

Reference 42

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This paper cites Distributional Smoothing with Virtual Adversarial Training.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Distributional Smoothing with Virtual Adversarial Training

Reference 43

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This paper cites Nascimento and Gustavo Carneiro.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Nascimento and Gustavo Carneiro

Reference 44

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This paper cites Reading digits in natural images with unsupervised feature learning.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Reading digits in natural images with unsupervised feature learning

Reference 45

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This paper cites Learning to Generate Reviews and Discovering Sentiment.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Learning to Generate Reviews and Discovering Sentiment

Reference 46

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Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Unsupervised representation learning with deep convolutional generative adversarial networks

Reference 47

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Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Semi-supervised learning with ladder networks

Reference 48

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This paper cites Semi- supervised self-training of object detection models.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Semi- supervised self-training of object detection models

Reference 49

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Observation bfe635f2-751b-4d18-9f08-de4e7a6d2a99 · outbound

This paper cites Moon: A mixed objective optimization network for the recognition of facial attributes.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Moon: A mixed objective optimization network for the recognition of facial attributes

Reference 50

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This paper cites Berg, and Li Fei-Fei.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Berg, and Li Fei-Fei

Reference 51

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This paper cites Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen

Reference 52

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This paper cites Simonyan and A.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Simonyan and A

Reference 53

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This paper cites Unsupervised and semi-supervised learning with categorical generative adversarial networks.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Unsupervised and semi-supervised learning with categorical generative adversarial networks

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:06:25.445465Z

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Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Least squares support vector machine classiﬁers

Reference 55

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This paper cites Going deeper with convolutions.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Going deeper with convolutions

Reference 56

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This paper cites Learning multi- instance deep discriminative patterns for image classiﬁcation.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Learning multi- instance deep discriminative patterns for image classiﬁcation

Reference 57

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This paper cites Video salient object de- tection via fully convolutional networks.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Video salient object de- tection via fully convolutional networks

Reference 58

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This paper cites Ranet: Ranking attention network for fast video object segmentation.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Ranet: Ranking attention network for fast video object segmentation

Reference 59

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Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Empirical Evaluation of Rectified Activations in Convolutional Network

Reference 60

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Reference 62

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This paper cites Real-world Noisy Image Denoising: A New Benchmark.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Real-world Noisy Image Denoising: A New Benchmark

Reference 63

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Reference 64

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Reference 65

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Reference 66

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Reference 67

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Reference 68

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This paper cites Sparse, collabora- tive, or nonnegative representation: Which helps pattern classiﬁcation? Pattern Recognition, 88:679 – 688, 2019.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Sparse, collabora- tive, or nonnegative representation: Which helps pattern classiﬁcation? Pattern Recognition, 88:679 – 688, 2019

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:06:25.061968Z

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Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Reweighted sparse subspace clustering

Reference 70

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This paper cites Star: A structure and texture aware retinex model, 2019.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Star: A structure and texture aware retinex model, 2019

Reference 71

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This paper cites Tstss: A two-stage training subset selection framework for cross version defect prediction.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Tstss: A two-stage training subset selection framework for cross version defect prediction

Reference 72

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This paper cites Cross version defect prediction with representative data via sparse subset selection.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Cross version defect prediction with representative data via sparse subset selection

Reference 73

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This paper cites Panda: Pose aligned networks for deep attribute modeling.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Panda: Pose aligned networks for deep attribute modeling

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:06:24.846992Z

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Observation d56cc893-ccfb-48a1-b8e3-0dfdc84e54fc · outbound

This paper cites newdna-prot: Prediction of dna-binding proteins by employing support vector machine and a comprehensive sequence representation.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition newdna-prot: Prediction of dna-binding proteins by employing support vector machine and a comprehensive sequence representation

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:06:24.822636Z

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This paper cites Energy-based Generative Adversarial Network.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Energy-based Generative Adversarial Network

Reference 76

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Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Semi-supervised regression with co- training

Reference 77

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This paper cites Introduction to semi-supervised learning.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Introduction to semi-supervised learning

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:06:24.761015Z

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Observation e65666a9-c5a6-4cbc-8c9e-0355bb2ee7a4 · outbound

This paper cites Zhuang, Z.

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Zhuang, Z

Reference 79

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