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. 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. Introduction and Use Cases. Derick . Winkworth. , Ed Henry and David Meyer. Agenda. Introduction and a Bit of History. So What Are Anomalies?. Anomaly Detection Schemes. Use Cases. Current Events. Q&A. Discriminative part-based models. Many slides based on . P. . . Felzenszwalb. Challenge: Generic object detection. Pedestrian detection. Features: Histograms of oriented gradients (HOG). Partition image into 8x8 pixel blocks and compute histogram of gradient orientations in each block. and Its Applications. . 基於電腦視覺之手指偵測及其應用. Yi-Fan Chuang. Advisor: Prof. Yi-Ping Hung. Prof. Ming-Sui Lee. Outline. Introduction. Related Work. Fingertip Detection and Tracking. Main Advantages. H . 2. 1. Fiber Optics Technology. . -Covert design. Caused no physical alteration to present building outlook. -Full Fiber Structure thus immune to lightning strike and EMI. A Synergistic . Approach. Wenxin. . Peng. Structure. Lane and . vehicle detection, localization and tracking . Reduce false positive results. Provide more information. Structure. Lane Detection. IPM – Inverse Perspective Mapping. DASFAA 2011. By. Hoang Vu Nguyen, . Vivekanand. . Gopalkrishnan. and Ira . Assent. Presented By. Salman. Ahmed . Shaikh. (D1). Contents. Introduction. Subspace Outlier Detection Challenges. Objectives of Research. 2. /86. Contents. Statistical . methods. parametric. non-parametric (clustering). Systems with learning. 3. /86. Anomaly detection. Establishes . profiles of normal . user/network behaviour . Compares . of Claw-pole Generators. Siwei Cheng. CEME Seminar, . April 2, 2012. Advisor . : Dr. Thomas G. Habetler. Condition Monitoring of Claw-pole Generators – Background. The heart of virtually all automotive electric power systems. 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. inWireless. Sensor Networks. Abstract. Wireless sensor networks are vulnerable to the node clone, and several distributed protocols have been proposed to . de¬tect. this attack. . However, they require too strong assumptions to be practical for large-scale, randomly deployed sensor networks. . Problem motivation. Machine Learning. Anomaly detection example. Aircraft engine features:. . = heat generated. = vibration intensity. …. (vibration). (heat). Dataset:. New engine:. Density estimation. Wedge Detection Using Resistivity, Refraction Tomography and Seismic Reflection. Sherif. . Hanafy. King Abdullah University of science and Technology (KAUST). Outline. Motivations. . Methodology. 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?.