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OF MALAYSIAS MODERNISATION A CRITIQUE OF DEVELOPMENTALISM Abdul Rahman Embong Emeritus Professor amp Principal Fellow at IKMAS UKM Keynote address at the International Conference on Reflection on Development and Beyond Exploring Alternatives to Social Progress . This controller is specifically engineered to run a standalone CDDVDBluray duplicator without additional computer or processing unit With a simple fourbutton interface and a LCD screen to display menu commands and realt ime status our CDDVDBluray Du Image AnyPlace combines bestinclass image processing with unique features to provide the AV professional and home theater enthusiast with unprecedented flexibility in projector setup and location Innovative Image AnyPlace keystone correction capabil Yilin. Wang. 11/5/2009. Background. Labeling Problem. Labeling: Observed data set (X) Label set (L). Inferring the labels of the data points. Most vision problems can be posed as labeling problems. Then . an array . of pixel values (colors) . The number . of elements . in this array is . width times height. Colors . can be . noted as. Indexed. . (looked up from a table) . or . True . Color. . By: . Georg Petschnigg Maneesh Agrawala Hugues Hoppe Richard Szeliski. Michael Cohen Kentaro Toyama,. Microsoft Corporation. Presented by. : Yael Amsterdamer. Advanced Topics in Visual Computing, Spring 2012. ELE 488 Final Project, Fall 2011. Princeton University. Ali JavadiAbhari. Watermarking. Why?. Fingerprinting (tracking). Indexing (search engines). Copyright protection and owner identification. Data hiding . Responsible Digital Data Processing. Diana Lim. University of Utah Molecular Medicine Program. Workflow. Data Collation. Photoshop. Illustrator. Proofing. Archiving. 2. Data Collation. Photoshop. Illustrator. Cryptographic Anonymity Project. Alan Le. A little background. Steganography originates from historical times. (invisible ink as an example). Steganography is the practice of concealing secret data in non-secret data. The “carrier” should look unsuspicious. . Recognition. Author : . Kaiming. He, . Xiangyu. Zhang, . Shaoqing. Ren, and Jian Sun. (accepted to CVPR 2016). Presenter : . Hyeongseok. Son. The deeper, the better. The deeper network can cover more complex problems. Nathan Gravlee. Digital Media. What is this? – . It make an image look for defined and hard-focused. It enhances detail!. When do I do this? – . Whenever an image is not quite clear as you would like. It can either greaten the details, or soften i. What is this?. It makes the image look crisper and the edges in the image more distinct.. When do I do this?. Whenever you want to emphasize texture or draw the viewers focus.. How do I use this?. Most image sharpening software tools work by applying something called an “. Learning Objectives. Be . able to describe when and why image corrections are appropriate or . necessary. Give . examples of some common approaches to image . correction. Understand the processing steps of Landsat data. The relevant features for the examination task are enhanced. The irrelevant features for the examination task are removed/reduced. Here the input and output image are both digital image in color or gray scale.. CS5670: Computer Vision. Reading. Szeliski. : Chapter 3.6. Announcements. Project 2 out, due Thursday, March 3 by 8pm. Do be done in groups of 2 – if you need help finding a partner, try Ed Discussions or let us know.