Deep learning algorithms are a subset of the machine learning algorithms, which aim at
discovering multiple levels of distributed representations. Recently, numerous deep learning …

Human activity recognition (HAR) aims to recognize activities from a series of observations
on the actions of subjects and the environmental conditions. The vision‐based HAR …

Deep learning's recent history has been one of achievement: from triumphing over humans
in the game of Go to world-leading performance in image classification, voice recognition …

Deep learning has recently been applied to scene labelling, object tracking, pose
estimation, text detection and recognition, visual saliency detection, and image …

Image representations, from SIFT and Bag of Visual Words to Convolutional Neural
Networks (CNNs), are a crucial component of almost any image understanding system …

Abstract The ImageNet Large Scale Visual Recognition Challenge is a benchmark in object
category classification and detection on hundreds of object categories and millions of …

Research in texture recognition often concentrates on the problem of material recognition in
uncluttered conditions, an assumption rarely met by applications. In this work we conduct a …

Image representations, from SIFT and bag of visual words to convolutional neural networks
(CNNs) are a crucial component of almost all computer vision systems. However, our …

This paper addresses the problem of generating possible object locations for use in object
recognition. We introduce selective search which combines the strength of both an …

摘要图像物体分类与检测是计算机视觉研究中的两个重要的基本问题, 也是图像分割, 物体跟踪,
行为分析等其他高层视觉任务的基础. 本文从物体分类与检测问题的基本定义出发, 首先从实例 …