Results 41 to 50 of about 4,829,196 (302)
NAG: Network for Adversary Generation [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 Adversarial perturbations can pose a serious threat for deploying machine learning systems. Recent works have shown existence of image-agnostic perturbations that can fool classifiers over most natural images. Existing methods present optimization approaches that solve for a fooling objective with an imperceptibility constraint to craft the ...
Konda Reddy Mopuri +3 more
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Sensors, 2020 Time series classification and forecasting have long been studied with the traditional statistical methods. Recently, deep learning achieved remarkable successes in areas such as image, text, video, audio processing, etc.
Kun Zhou +3 more
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Application of deep learning in recognition of accrued earnings management
Heliyon, 2023 We choose the sample data in Chinese capital market to compare the measurement effect of earnings management with Deep Belief Network, Deep Convolution Generative Adversarial Network, Generalized Regression Neural Network and modified Jones model by ...
Jia Li, Zhoutianyang Sun
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Regularized Generative Adversarial Network [PDF]
SSRN Electronic Journal, 2021 18 pages. Comments are welcome!
Gabriele Di Cerbo +2 more
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Adversarial Examples Detection for XSS Attacks Based on Generative Adversarial Networks
IEEE Access, 2020 Models based on deep learning are prone to misjudging the results when faced with adversarial examples. In this paper, we propose an MCTS-T algorithm for generating adversarial examples of cross-site scripting (XSS) attacks based on Monte Carlo tree ...
Xueqin Zhang +4 more
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Ensemble Adversarial Example Defense Based on Generative Adversarial Network
工程科学与技术, 2022 Given the bottlenecks of existing adversarial example defense schemes, such as insufficient defense capability and high time consumption, an ensemble adversarial example defense scheme based on the generative adversarial network was proposed in this ...
Tianjie CAO +5 more
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Dairy Goat Image Generation Based on Improved-Self-Attention Generative Adversarial Networks
IEEE Access, 2020 The lack of long-range dependence in convolutional neural networks causes weaker performance in generative adversarial networks(GANs) with regard to generating image details. The self-attention generative adversarial network(SAGAN) use the self-attention
Huan Li, Jinglei Tang
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Компьютерная оптикаSingle-pixel imaging is a promising image acquisition method that provides an alternative to traditional imaging methods using multi-pixel matrices. However, algorithmic image reconstruction from measurements of a single-pixel camera is a non-trivial ...
D.V. Babukhin, A.A. Reutov, D.V. Sych
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Noise robust chi-square generative adversarial network [PDF]
, 2020 Aiming at the obvious difference of image quality generated by generative adversarial network under different noises,a chi-square generative adversarial network (CSGAN) was proposed.Combing the advantages of quantification sensitivity and sparse ...
Hongjun LI, Shibing ZHANG, Chaobo LI
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Improved Wasserstein conditional generative adversarial network speech enhancement
EURASIP Journal on Wireless Communications and Networking, 2018 The speech enhancement based on the generative adversarial network has achieved excellent results with large quantities of data, but performance in the low-data regime and tasks like unseen data learning still lag behind.
Shan Qin, Ting Jiang
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