PPT-Curvilinear Structure Segmentation

Sebastian Sotela Introduction CS2Net Methodology Experimental Setup Results and Discussion ERNet Methodology Experimental Setup Results and Discussion Personal Review Takeaways References. - continuous and discrete approaches . 2 : . Exact . and approximate techniques. . - non-submodular and high-order problems. 3: Multi-region segmentation (Milan). - high-dimensional applications . Approach for Topology-Change-Aware Video Matting. Jinlong Ju. 1. , Jue Wang. 3. , . Yebin. Liu. 1. , . Haoqian. Wang. 2. , . Qionghai. Dai. 1. Department of Automation, Tsinghua University, China. 6. Objectives. Explain STP Process. Segmentation Bases. Target Segment Criteria. Elements of Effective Positioning. Creating Brand Value/Equity. STP Marketing & the Evolution of Marketing Strategy. Sungsu. Lim. AALAB, KAIST. Image Segmentation. Computer vision. : make machine to see or to understand/ . interpret . the scenes (images & videos) like human do.. Image segmentation. is one of the most challenging issues in computer vision.. Daphne . Laino. and Danielle Roy. What is Segmentation?. Process of partitioning an image into segments. Segments are called . superpixels. Superpixels. are made up several pixels that have similar properties. By: A’laa . Kryeem. Lecturer: . Hagit. Hel-Or. What is . Segmentation from . Examples. ?. Segment an image based on one (or more) correctly segmented image(s) assumed to be from the same . domain. 1. NADINE GARAISY. GENERAL DEFINITION. 2. A drainage basin or watershed is an extent or an area of land where surface water from rain melting snow or ice converges to a single point at a lower elevation, usually the exit of the basin, where the waters join another . Anurag Arnab. Collaborators: . sadeep. . Jayasumana. , . shuai. . zheng. , Philip . torr. Introduction. Semantic Segmentation. Labelling every pixel in an image. A key part of Scene Understanding. Yassine Benajiba. 1. and . Imed. Zitouni. 2. 1 CCLS, Columbia University. 2 IBM T.J. Watson Research Center. ybenajiba@ccls.columbia.edu. , . izitouni@us.ibm.com. . Outline. The Arabic Language. ATB vs. Morph segmentation. via Subspace Clustering. Ruizhen. Hu . Lubin. Fan . Ligang. Liu. Co-segmentation. Hu et al.. Co-Segmentation of 3D Shapes via Subspace Clustering. 2. Input. Co-segmentation. Hu et al.. 1. Global Marketing. Chapter 7. Market Segmentation. Represents an effort to identify and categorize groups of customers and countries according to common characteristics. 7-. 2. Targeting. The process of evaluating segments and focusing marketing efforts on a country, region, or group of people that has significant potential to respond. 2015. 2. 12.. Jeany Son. References. Bottom-up Segmentation for Top-down . Detection, CVPR 2013. Segmentation-aware Deformable Part Models, CVPR 2014. 2. Prior Works on Segmentation & Recognition. Concerned with the individuals, institutions, or groups of individuals or institutions that have similar needs that can be met by a particular product offering. The goal is to identify specific customer needs, then design a marketing program that can satisfy those needs.. Kaushik . Nandan. 1. Contents:. Introduction. Related . Work. Segmentation as Selective . Search. Object Recognition . System. Evaluation. Conclusions. References. 2. 1. Introduction. Object recognition: determining .