PPT-Detection of Qademah

Detection of Qademah Fault using Geophysical Methods Sherif Hanafy King Abdullah University of science and Technology KAUST 7 th Gulf Seismic Forum 2012 24 January 2012 Outline Motivations Study Area. 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 UTSA. Moheeb Abu Rajab, Lucas Ballard, Nav Jagpal, Panayiotis Mavrommatis,. Daisuke Nojiri, Niels Provos, Ludwig Schmidt. Present by Li Xu. 2. Detecting Malicious Web Sites. Which pages are safe URLs for end users?. Chapter 12. Target Microorganisms for Molecular-Based Testing. Those that are difficult or time-consuming to isolate. e.g., . Mycobacteria. Hazardous organisms. e.g., . Histoplasma. , . Coccidioides. Ross . Girshick. , Jeff Donahue, Trevor Darrell, . Jitandra. Malik (UC Berkeley). Presenter: . Hossein. . Azizpour. Abstract. Can CNN improve . s.o.a. . object detection results?. Yes, it helps by learning rich representations which can then be combined with computer vision techniques.. by oversampling of OMI data: Implications for TEMPO. Lei Zhu and Daniel J. Jacob. HCHO observations from space constrain emissions. of highly reactive volatile organic compounds (HRVOCs). HRVOCs. HCHO. Field Data Example. G. . Dutta. , A. . . AlTheyab. , S. . Hanafy. , G. Schuster. King Abdullah University of Science and Technology, Saudi Arabia. September 19, 2012. Outline. Motivation. Background. 2011/12/08. Robot Detection. Robot Detection. Better Localization and Tracking. No Collisions with others. Goal. Robust . Robot . Detection. Long . Range. Short. . Range. Long Range. C. urrent . M. ethod. Mycotoxin. in Wheat. Start date: . September. 201. 0. Duration: . 36. months. Website: . www.. mycohunt. .. eu. Funding Scheme: . FP7 . Research. . for . the Benefit of . SME. -AGs. The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 286522.. Presenter: Dave McDonald. Rosco Vision Systems. Agenda. Background. Cameron Gulbransen Kids Transportation Safety Act of 2007. Abigail’s Law – New Jersey. Current Technologies. Electronic Based Detection. CS 469: Security Engineering. These slides are modified with permission from Bill Young (. Univ. of Texas). Coming up: Intrusion Detection. 1. Intrusion . Detection. An . intrusion detection system . State-of-the-art face detection demo. (Courtesy . Boris . Babenko. ). Face detection and recognition. Detection. Recognition. “Sally”. Face detection. Where are the faces? . Face Detection. What kind of features?. The correspondence problem. A general pipeline for correspondence. If sparse correspondences are enough, . choose points for which we will search for correspondences (feature points). For each point (or every pixel if dense correspondence), describe point using a . What is Edge Detection?. Identifying points/Edges . in a digital image at which the image brightness changes sharply . or . has . discontinuities. . - Edges are significant local changes of intensity in an image.. Xindian. Long. 2018.09. Outline. Introduction. Object Detection Concept and the YOLO Algorithm. Object Detection Example (CAS Action). Facial Keypoint Detection Example (. DLPy. ). Why SAS Deep Learning .