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An Ultra-Low-Power Image Signal Processor for Hierarchical Image Recognition With Deep Neural Networks

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An Ultra-Low-Power Image Signal Processor for Hierarchical Image Recognition With Deep Neural Networks

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Deep Learning Generalization with Limited and Noisy Labels

BLACK-BOX ATTACKS ON IMAGE ACTIVITY PREDICTION AND ITS NATURAL LANGUAGE EXPLANATIONS

Fixing the problems of deep neural networks will require better training data and learning algorithms

Regularization of polynomial networks for image recognition

Regularization of polynomial networks for image recognition

Improving the Training of Compact Neural Networks for Visual Recognition

Impulsive noise removal via a blind CNN enhanced by an iterative post-processing

SafeAMC: Adversarial training for robust modulation classification models

Stop Wasting my FLOPS: Improving the Efficiency of Deep Learning Models

Tracking and Relative Localization of Drone Swarms With a Vision-Based Headset

Deep Learning Generalization with Limited and Noisy Labels

Fixing the problems of deep neural networks will require better training data and learning algorithms

Regularization of polynomial networks for image recognition

Stop Wasting my FLOPS: Improving the Efficiency of Deep Learning Models

Improving the Training of Compact Neural Networks for Visual Recognition

Tracking and Relative Localization of Drone Swarms With a Vision-Based Headset

Impulsive noise removal via a blind CNN enhanced by an iterative post-processing

BLACK-BOX ATTACKS ON IMAGE ACTIVITY PREDICTION AND ITS NATURAL LANGUAGE EXPLANATIONS

Regularization of polynomial networks for image recognition

SafeAMC: Adversarial training for robust modulation classification models