[1] Z. Zhou, Y. Huang, W. Wang, L. Wang, T. Tan, Ieee, See the Forest for the Trees: Joint Spatial and Temporal Recurrent Neural Networks for Video-based Person Re-identification, 30th Ieee Conference on Computer Vision and Pattern Recognition, (Ieee…

Introduction 在视频序列中,有些帧由于被严重遮挡,需要被尽可能的“忽略”掉,因此本文提出了时间注意力模型(temporal attention model,TAM),注重于更有相关性的帧. 常规的矩阵学习通常用特征的距离来进行计算,但忽视了帧之间的差异,上图可以看出,本文的方法考虑了相邻帧的空间差异,即空间循环模型(spatial recurrent model,SRM). The proposed method (1)总体框架: 输入的视频序列为:,输入为视频序列三元组,首先通过C…

转自 http://blog.csdn.net/xingzhedai/article/details/53144126 更多参考:http://blog.csdn.net/mafeiyu80/article/details/51446558 http://blog.csdn.net/caimouse/article/details/70225998 http://kubicode.me/2017/05/15/Deep%20Learning/Understanding-about-RNN/ RNN…

论文地址:基于分层递归神经网络的嵌入式设备轻量化在线降噪 引用格式:Schröter H, Rosenkranz T, Zobel P, et al. Lightweight Online Noise Reduction on Embedded Devices using Hierarchical Recurrent Neural Networks[J]. arXiv preprint arXiv:2006.13067, 2020. 摘要 基于深度学习的降噪算法已经证明了它们的成功,尤其是对非平…

Building your Recurrent Neural Network - Step by Step Welcome to Course 5's first assignment! In this assignment, you will implement your first Recurrent Neural Network in numpy. Recurrent Neural Networks (RNN) are very effective for Natural Language…

RNN(Recurrent Neural Networks)公式推导和实现 http://x-algo.cn/index.php/2016/04/25/rnn-recurrent-neural-networks-derivation-and-implementation/ 2016-04-25 分类:Deep Learning / NLP / RNN 阅读(6997) 评论(7)  本文主要参考wildml的博客所写,所有的代码都是python实现.没有使用任何深度学习的工具,公式推导虽然枯燥,…

Conditional Random Fields as Recurrent Neural Networks ICCV2015    cite237 1摘要: 像素级标注的重要性(语义分割 图像理解)-- 现在开始利用DL----但DL无法描述visual objects----本文引入新型的CNN,将CNN与CRF概率图模型结合---用高斯pairwise势函数定义的CRF作为RNN,记为CRF-RNN----将其作为CNN的一部分,使得深度模型同时具有CNN和CRF的特性,同时本文算法完美结…

Improvise a Jazz Solo with an LSTM Network Welcome to your final programming assignment of this week! In this notebook, you will implement a model that uses an LSTM to generate music. You will even be able to listen to your own music at the end of th…

动机(Motivation) 在自动语音识别(Automated Speech Recognition, ASR)中,只是把语音内容转成文字,但是人们对话过程中除了文本还有其它重要的信息,比如语调,情感,响度.这些信息对于语音的理解也是很重要的.本文关注其中一个点,如何识别出语音的情感,即语音情感识别(Speech Emotion Recognition, SER). 语音情感识别的三个难点 1. 感情是主观的:不同人对于同一段语音,理解出的情感不尽相同,而且存在一定的文化差异. 2. 感情在语…

(没太听明白,下次重新听一遍) 1. Recurrent Neural Networks…