Paper Reading:Deep Neural Networks for Object Detection

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Paper Reading:Deep Neural Networks for Object Detection

发表时间:2013 发表作者:(Google)Szegedy C, Toshev A, Erhan D 发表刊物/会议:Advances in Neural Information Processing Systems(NIPS) 本文实现了一种利用DNN来做目标检测的方法.当时,CNN等深度学习在识别上面做的还挺好,但是在目标检测上面没有特别突出的结果.本文中作者把目标检测看做一个回归问题,回归目标窗口(BoundingBox)的位置,寻找一张图片当中目标类别和目标出现的位置. 作者在Imag…

Paper Reading:Deep Neural Networks for YouTube Recommendations

论文:Deep Neural Networks for YouTube Recommendations 发表时间:2016 发表作者:(Google)Paul Covington, Jay Adams, Emre Sargin 发表刊物/会议:RecSys 论文链接:论文链接这篇论文是google的YouTube团队在推荐系统上DNN方面的尝试,发表在16年9 月的RecSys会议.本文就focus在YouTube视频推荐的DNN算法,文中不但详细介绍了Youtube推荐算法和架构细节,还给了…

Deep Neural Networks for Object Detection（翻译）

0 - Abstract 深度神经网络(DNNs)最近在图像分类任务上表现出了突出的性能.在这篇文章中,我们进一步深入探究使用DNNs进行目标检测的问题,这个问题不仅需要对物体进行分类,并且还需要对各种各样类别的物体进行精确定位.我们提出了简单但依然有效的将目标检测问题形式化为回归问题从而来对物体边界框进行定位.我们提出了一个多尺度推理程序(模型?),它可以通过应用少量网络层来产生高分辨率的具有小误差的目标检测.并在Pascal VOC上展示了当前最好方法的效果. 1 - Introductio…

Coursera, Deep Learning 4, Convolutional Neural Networks, week3, Object detection

学习目标 Understand the challenges of Object Localization, Object Detection and Landmark Finding Understand and implement non-max suppression Understand and implement intersection over union Understand how we label a dataset for an object detection appli…

On Explainability of Deep Neural Networks

On Explainability of Deep Neural Networks « Learning F# Functional Data Structures and Algorithms is Out! On Explainability of Deep Neural Networks During a discussion yesterday with software architect extraordinaire David Lazar regarding how every…

目标检测--Scalable Object Detection using Deep Neural Networks(CVPR 2014)

Scalable Object Detection using Deep Neural Networks 作者: Dumitru Erhan, Christian Szegedy, Alexander Toshev, and Dragomir Anguelov 引用: Erhan, Dumitru, et al. "Scalable object detection using deep neural networks." Proceedings of the IEEE Confere…

Paper Reading: Relation Networks for Object Detection

Relation Networks for Object Detection笔记写在前面:关于这篇论文的背景知识,请参考我前面的两篇随笔(<关于目标检测>和<关于注意力机制>) 摘要: 所有最先进的物体检测系统仍然依赖于单独识别物体实例, 在学习过程中并没有利用它们的关系.(背景) 这个工作提出了一个目标关系模块.它通过它们的外观特征和几何图形之间的交互来同时处理一组物体,从而对它们之间的关系进行建模.它是轻量级的和就地(in-place)这里的relation module是…

Must Know Tips/Tricks in Deep Neural Networks

Must Know Tips/Tricks in Deep Neural Networks (by Xiu-Shen Wei) Deep Neural Networks, especially Convolutional Neural Networks (CNN), allows computational models that are composed of multiple processing layers to learn representations of data with…

Must Know Tips/Tricks in Deep Neural Networks (by Xiu-Shen Wei)

http://lamda.nju.edu.cn/weixs/project/CNNTricks/CNNTricks.html Deep Neural Networks, especially Convolutional Neural Networks (CNN), allows computational models that are composed of multiple processing layers to learn representations of data with mul…

（转）Understanding, generalisation, and transfer learning in deep neural networks

Understanding, generalisation, and transfer learning in deep neural networks FEBRUARY 27, 2017 This is the first in a series of posts looking at the ‘top 100 awesome deep learning papers.’ Deviating from the normal one-paper-per-day format, I’ll ta…