PPT-Salient Object Detection by Composition

Jie Feng 1 Yichen Wei 2 Litian Tao 3 Chao Zhang 1 Jian Sun 2 1 Key Laboratory of Machine Perception Peking University 2 Microsoft Research Asia 3 Microsoft Search Technology Center Asia. we have evolved the process and methodology of leak detection and location into a science and can quickly and accurately locate leaks in homes, office buildings, swimming pools and space, as well as under streets and sidewalks, driveways, asphalt parking lots and even golf courses. 02nT Faster cycle rates Up to 10Hz Longer range detection Pros brPage 5br Magnetometers Magnetometers Large distant targets mask small local targets Difficult to pick out small target due to background noise No sense of direction of target on single Developed by:. SUYOG System & Software Pvt. Ltd.. Powered by Tally.ERP 9. Seamlessly Integrated with Tally.ERP 9. User Friendly . Adopts . latest statutory updates . Professional advise by Industry Experts. . Each . feature set increases accuracy over the 69% baseline accuracy. .. Word Prominence Detection using Robust yet Simple Prosodic Features. Prosodic Features . ( . ** denotes novel features. ). Peng. Wang. 1. . Jingdong. Wang. 2. Gang Zeng. 1. . Jie. Feng. 1. Hongbin. Zha. 1. . Shipeng. Li. 2. 1. Key Laboratory on Machine Perception, Peking University . 2. Microsoft Research Asia. Outline. Stas. . Goferman. Lihi. . Zelnik. -Manor. Ayellet. Tal. What is saliency?. …. Please describe this picture. Picture description. Man in a flower field. In the fields. Spring blossom. Please describe this picture. Compositional bias of salient object detection benchmarking. Xiaodi. . Hou. K-Lab, Computation and Neural Systems. California Institute of Technology. for the Crash Course on Visual Saliency Modeling:. Jianming. Zhang, Stan . Sclaroff. , . Zhe. . lin. , . Xiaohui. Shen, Brian Price, . Radomir. . Mech. IEEE International Conference on Computer Vision (ICCV), 2015. IEEE International Conference on Computer Vision (ICCV), 2015, Santiago, Chile. Leo Zhu. CSAIL MIT . Joint work with Chen, Yuille, Freeman and Torralba . 1. Ideas behind . Recursive Composition . How to deal with image complexity. A general framework for different vision tasks. Rich representation and tractable computation. Salient Management Company 203 Colonial Drive, Horseheads, NY 14845 USA phone 607.739.4511 / 800.447.1868 fax 607 .739.4045 www.salient.com MANAGEMENT COMPANY We’ll make your in Authors:. Farnaz Shariat , . Riadh Ksantini, . Boubakeur . Boufama. shariatf@uwindsor.ca. ksantini@uwindsor.ca. boufama@uwindsor.ca. University of Windsor. May 2009. 2. Presentation Outline . Introduction . Before deep . convnets. Using deep . convnets. PASCAL VOC. Beyond sliding windows: Region proposals. Advantages:. Cuts . down on number of regions detector must . evaluate. Allows detector to use more powerful features and classifiers. Bangpeng Yao and Li Fei-Fei. Computer Science Department, Stanford University. {bangpeng,feifeili}@cs.stanford.edu. 1. Robots interact with objects. Automatic sports commentary. “Kobe is dunking the ball.”. Yonggang Cui. 1. , Zoe N. Gastelum. 2. , Ray Ren. 1. , Michael R. Smith. 2. , . Yuewei. Lin. 1. , Maikael A. Thomas. 2. , . Shinjae. Yoo. 1. , Warren Stern. 1. 1 . Brookhaven National Laboratory, Upton, USA.