PPT-R-CNN

By Zhang Liliang Main idea good features are no enough VOC07 mAP351 gt 585 Overview 1 the model of RCNN 2 the result of RCNN 3 some discussions Visualizing learned feature in CNN. If you dont find the answers at each stop be sure to ask your tour guide INTRODUCTION THEATER Lear n about the evolution of a news story from interviews in the field to satellites far beyond Earths atmosphere to newsrooms and then to televisions and These are the words nine young North Korean defectors had waited years to hear having traveled thousands of miles Unfortunately it was a lie The tragic story of this group of youngsters aged between 15 and 23 takes us back a few years when one by on Analysis of CNN and The Fox News Networks’ framing of the Muslim Brotherhood during the Egyptian revolution in 2011 Kelsey Glover * Strategic Communications Elon University Abstract As the worl -- Apple has been accused of kowtowing to the Chinese government by pulling from its China App Store a product enabling users to circumvent firewalls and access restricted sites.. Hong Kong (CNN). -- Apple has been accused of kowtowing to the Chinese government by pulling from its China App Store a product enabling users to circumvent firewalls and access restricted sites.. WHO CONTRIBUTED IMMENSELY TO THE DEVELOPMENT OF INTERNATIONAL BROADCAST MEDIA. . . Wolf Blitzer. . Dan Rather. . Anderson Cooper. . Howard . Cosell. . . Timothy . Russert. .. . Christiane . Amanpou. Moitreya Chatterjee, . Yunan. . Luo. Image Source: Google. Outline – This Section. Why do we need Similarity Measures. Metric Learning as a measure of Similarity. Notion of a metric. Unsupervised Metric Learning. . hongliang. . xue. Motivation. . Face recognition technology is widely used in our lives. . Using MATLAB. . ORL database. Database. The ORL Database of Faces. taken between April 1992 and April 1994 at the Cambridge University Computer . Carl . Doersch. Joint work with Alexei A. . Efros. . & . Abhinav. Gupta. ImageNet. + Deep Learning. Beagle. - Image Retrieval. - Detection (RCNN). - Segmentation (FCN). - Depth Estimation. - …. Yunchao. Wei, Wei Xia, . Junshi. Huang, . Bingbing. Ni, Jian Dong, Yao Zhao, Senior Member, IEEE . Shuicheng. Yan, Senior Member, IEEE. 2014. . arXiv. IEEE. . Short Papers. . HCPIssue. Date: Sept. 1 2016. Deformable Part Models with CNN Features. Pierre-André . Savalle. , . Stavros . Tsogkas. , George Papandreou, Iasonas Kokkinos. From HOG to CNN features. Detection . performance of C-DPM. Method. . Moitreya Chatterjee, . Yunan. . Luo. Image Source: Google. Outline – This Section. Why do we need Similarity Measures. Metric Learning as a measure of Similarity. Notion of a metric. Unsupervised Metric Learning. Deep Learning Architectures. feed-forward . networks. auto-encoders (output want to recover input image, middle layer smaller - use results of middle layer for compression. ). recurrent neural networks (RNNs) (backward feeding at run time as part of input into middle . 12/8/16. BGU, DNN course 2016. Sources. Main paper. “. Rich . feature hierarchies for accurate object detection and semantic . segmentation. ”, . Ross . Girshick. , Jeff Donahue, Trevor Darrell, . Paper ID: 8762. K. M. Naimul Hassan. , Md. Shamiul . Alam. . Hridoy. , Naima Tasnim, . Atia. . Faria. Chowdhury, Tanvir . Alam. Roni, Sheikh Tabrez, Arik . Subhana. , Celia Shahnaz. Department of Electrical and Electronic Engineering (EEE),.