Neural network compressionTransfer learningSeveral practical difficulties arise when trying to apply deep learning to image-based industrial inspection tasks: training datasets are difficult to obtain, each imag
Collection of recent methods on (deep) neural network compression and acceleration. - MingSun-Tse/Efficient-Deep-Learning
Coupled Compression Methods 与剪枝,知识蒸馏或者硬件设计结合(这个方面目前研究还很少) Quantized Training 也许量化最重要的用途是用半精度加速神经网络训练[41,72,77,175]。这使得使用更快、更节能的低精度逻辑进行训练成为可能。 但是很难远远超过INT8训练的速度 且目前工作需要大量的超参数调整,并且使用INT8精度可...
The `Internet of Things' has brought increased demand for AI-based edge computing in applications ranging from healthcare monitoring systems to autonomous vehicles. Quantization is a powerful tool to address the growing computational cost of such applications, and yields significant compression over full...
Image Compression using Artificial Neural Networks (ANN) is significantly different than compressing raw binary data. General purpose compression programs can be used to compress images, but the result is less than optimal. This is because images have certain statistical properties which can be ...
image compressionneural network back propagationneural network radial basis functionImage compression technique is used to reduce the number of bits required in representing image, which helps to reduce the storage space and transmission cost. Image compression techniques are widely used in many ...
关键词:deep learning(深度学习), neural network(神经网络), deep neural networks (DNN)(深度神经网络), convolutional neural networks (CNN)(卷积神经网络), artificial intelligence (AI)(“人工智能”), efficient processing(高效处理), accelerator architecture(加速器架构), hardware/software co-design(硬/软...
EagleEye 2020-ECCV-EagleEye: Fast Sub-net Evaluation for Efficient Neural Network Pruning 来源:ChenBong 博客园 Institute:Dark Matter AI Inc.、Sun Yat-sen Un
compressionNETWORKQUANTIZATIONDeep convolutional neural networks(DCNNs)have shown outstanding performance in the fields of computer vision,natural language processing,and complex system analysis.With the improvement of performance with deeper layers,DCNNs incur higher computational complexity and larger storage ...
TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework, which contains features like neural architecture search, pruning, quantization, model conversion and etc. It has been utilized for the deployment on devices such as Tmall Genie, Haier TV, Youku video, face...