综述：A survey of recent advances in visual feature detection（Author's Accepted Manuscript）

翻译 一项关于视觉特征检测最新进展的调查:综述 摘要 - 原文地址:https://www.cnblogs.com/Alliswell-WP/p/TranslationOfPapers_Review004.html

翻译 特征提取与描述算法的最新进展:综述 摘要 - 计算机视觉是当今信息技术中最活跃的研究领域之一.让机器和机器人能够以视线的速度看到和理解周围的世界,创造出无穷无尽的潜在应用和机会.特征检测和描述算法确实可以被认为是这种机器和机器人眼睛的视网膜.然而,这些算法通常是计算密集型的,这使得它们无法实现视觉实时性能的速度.此外,它们的能力不同,有些人可能会因为特定类型的输入而与其他人相比更有利于工作.因此,必须紧凑地报告其利弊,以及他们的表现和最近的进展.本文致力于全面概述特征检测和描述算法的最新进

high bias if the robot has learnt something (no changes appear with iterations) however, in the real world tasks, the task could change a little bit, then the robot will failed to generalize. no matter how well we train the robot in situations, there

题目:车联网信道建模和测量的最新进展及未来挑战 这篇论文属于介绍性文章,主要介绍阐述了V2V信道的建模与测量,并提出未来V2V信道研究的挑战. 论文主要分为四个部分,第一部分是摘要和简介,讲述了这篇论文的梗概及车联网的发展情况:第二部分系统地介绍了V2V信道的测量活动,根据载波频率.频率选择性.路况环境.天线.TX和RX的运动方向.信道统计量方面分别阐述了信道测量活动:第三部分讲述了车联网中典型的模型:GBDMs(几何确定性模型).NGSMs(非几何随机性模型)和GBSMs(几何随机性模型):(

这篇文章目前发表在arxiv,日期:20180309. 这是一篇针对多种综合性信息的视觉显著性检测的综述文章. 注:有些名词直接贴原文,是因为不翻译更容易理解.也不会逐字逐句都翻译,重要的肯定不会错过^_^.我们的目的是理解文章思想,而不是为了翻译而纯粹翻译.翻译得不好,敬请包涵O(∩_∩)O~ 欢迎同道中人QQ交流:1505543113 abstract: 随着采集技术( acquisition technology)的发展,许多综合性信息(comprehensive information)

Active Learning Two Faces of Active Learning, Dasgupta, 2011 Active Learning Literature Survey, Settles, 2010 Applications A Survey of Emerging Approaches to Spam Filtering, Caruana, 2012 Ambient Intelligence: A Survey, Sadri, 2011 A Survey of Online

Survey Recent Advances in Efficient Computation of Deep Convolutional Neural Networks, [arxiv '18] A Survey of Model Compression and Acceleration for Deep Neural Networks [arXiv '17] Quantization The ZipML Framework for Training Models with End-to-En

IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM) 2014 Industry Track Call for Papers Beijing China August 17-20, 2014Home Page: www.asonam2014.org Full paper/short paper/extended abstract submission deadlin

The year in AI: 2019 ML/AI advances recap 2020-01-26 11:47:14 Source: https://medium.com/@xamat/the-year-in-ai-2019-ml-ai-advances-recap-c6cc1d902d5 It has become somewhat of a tradition for me to do an end-of-year retrospective of advances in AI/ML