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Do Noises Bother Human and Neural Networks In the Same Way? A Medical Image Analysis Perspective
Deep learning had already demonstrated its power in medical images, incl...
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Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation
The state-of-art DNN structures involve intensive computation and high m...
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Thread Batching for High-performance Energy-efficient GPU Memory Design
Massive multi-threading in GPU imposes tremendous pressure on memory sub...
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Machine Vision Guided 3D Medical Image Compression for Efficient Transmission and Accurate Segmentation in the Clouds
Cloud based medical image analysis has become popular recently due to th...
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Progressive DNN Compression: A Key to Achieve Ultra-High Weight Pruning and Quantization Rates using ADMM
Weight pruning and weight quantization are two important categories of D...
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E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs
Recurrent Neural Networks (RNNs) are becoming increasingly important for...
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Defensive Dropout for Hardening Deep Neural Networks under Adversarial Attacks
Deep neural networks (DNNs) are known vulnerable to adversarial attacks....
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ADAM-ADMM: A Unified, Systematic Framework of Structured Weight Pruning for DNNs
Weight pruning methods of deep neural networks (DNNs) have been demonstr...
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A Systematic DNN Weight Pruning Framework using Alternating Direction Method of Multipliers
Weight pruning methods for deep neural networks (DNNs) have been investi...
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On the Universal Approximation Property and Equivalence of Stochastic Computing-based Neural Networks and Binary Neural Networks
Large-scale deep neural networks are both memory intensive and computati...
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MT-Spike: A Multilayer Time-based Spiking Neuromorphic Architecture with Temporal Error Backpropagation
Modern deep learning enabled artificial neural networks, such as Deep Ne...
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PT-Spike: A Precise-Time-Dependent Single Spike Neuromorphic Architecture with Efficient Supervised Learning
One of the most exciting advancements in AI over the last decade is the ...
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Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial Examples
Deep Neural Networks (DNNs) have achieved remarkable performance in a my...
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DeepN-JPEG: A Deep Neural Network Favorable JPEG-based Image Compression Framework
As one of most fascinating machine learning techniques, deep neural netw...
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Security Analysis and Enhancement of Model Compressed Deep Learning Systems under Adversarial Attacks
DNN is presenting human-level performance for many complex intelligent t...
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2.4GHZ Class AB power Amplifier For Healthcare Application
The objective of this research was to design a 2.4 GHz class AB Power Am...
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