We test neural network models with L ANCE onrepresentative image classif i cation datasets, including SVHN,CIFAR, and ImageNet. The experimental results show thatour 8-bit quantized Winograd convolution improves the per-formance by up to 2.40× over the full-precision convolutionwith trivial ...
(ECG);arrhythmia;deepneuralnetwork;machinelearning;deeplearning;PhysioBank;kaggle;python;TensorFlow1.IntroductionElectrocardiography(ECG)isaprocedureusedtoevaluatetheelectricalactivityoftheheartwithreferencetotimebyinsertionofelectrodesontheskin.Theelectrodescanrecognizetrivialelectricalchangesinskin.ECGdetectsphysicalcardiac...
Purpose:In this work, we explore to use very deep convolutional neural network (CNN) for the automatic classification of diabetic retinopathy using color f... Kele Xu,L Zhu,R Wang,... - 《Medical Physics》 被引量: 5发表: 2016年 Classification of Diabetic Retinopathy Using Deep Neural Netwo...
只是这个toolbox的代码和《Notes on Convolutional Neural Networks》里有些不一样的是这个toolbox在subsampling(也就是pooling层)没有加sigmoid激活函数,只是单纯地pooling了一下,所以这地方还需仔细辨别,这个toolbox里的subsampling是不用计算gradient的,而在Notes里是计算了的 还有这个toolbox没有Combinations of Feature...
【论文笔记】Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition 地址:https://arxiv.org/pdf/2006.11538.pdf github:https://github.com/iduta/pyconv 目前的卷积神经网络普遍使用3×3的卷积神经网络,通过堆叠3×3的卷积核和下采样层,会在减少图像的大小的同时增加感受野,使用小...
//papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf）在...
Gated Recurrent Convolution Neural Network for OCR This project is an implementation of the GRCNN for OCR. For details, please refer to the paper: https://papers.nips.cc/paper/6637-gated-recurrent-convolution-neural-network-for-ocr.pdf Update The journal version of GRCNN has been accepted by...
文章链接:http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf 在2012 Imagenet LSVRC比赛中,Alexnet以15.3%的top-5 错误率轻松拔得头筹(第二名top-5错误率为26.2%)。由此,DCNN的潜力受到广泛认可,一炮而红... ...
【医学+深度论文:F09】2018 Deep Convolution Neural Network for Accurate Diagnosis of Glaucoma Using Digital,程序员大本营,技术文章内容聚合第一站。
The convolution neural network implemented on hardware has a processing time of approximately 5.7 ms and a power consumption of 1.868 W. Keywords: non-intrusive load monitoring; convolution neural network; V-I trajectory; hardware classifier; FPGA 1. Introduction Non-intrusive load monitoring (NILM)...