PPT-3/13/2012 1 Filtering Options

Processing The PARIS File Deuces Wild FILTERING OPTIONS FOR YOUR PARIS FILE Stephen Bach New York State Office of Temporary and Disability Services Bureau of Program Integrity Mark Zaleha Ohio Department of Job and Family Services Bureau of Program Integrity. Convolution is a general purpos e filter effect for images Is a matrix applied to an image and a mathematical operation comprised of integers It works by determining the value of a central pixel by adding the weighted values of all its neighbors tog . Advanced Shadow Maps. CSE 781. Prof. Roger Crawfis. Shadow Map Enhancements. Two main research thrusts.. Shadow Map Filtering. Variance Shadow Maps. Convolution Shadow Maps. Exponential Shadow Maps. Deep Packet Inspection. Artyom. . Churilin. Tallinn University of Technology 2011. Web filtering & DPI. Web filtering (content control) . is a way control . what content is permitted to a . user. . Overview of Filtering. Convolution. Gaussian filtering. Median filtering. Overview of Filtering. Convolution. Gaussian filtering. Median filtering. Motivation: Noise reduction. Given a camera and a still scene, how can you reduce noise?. Temporal filtering . – visual response slower than input signal. . 2. Spatial filtering . – local signals are combined across space to varying degrees.. . . 3. Light adaptation . – retina modifies responsiveness depending on average light level.. Lecture 20: Image Enhancement in Frequency Domain. Recap of Lecture 19. Spatial filtering. Mean Filter. Non-Local Mean Filter. Median Filter. Unsharp. Masking. Adaptive . Unsharp. Masking. Outline of Lecture 20. Chapter 6. Introduction. Technical controls – essential. Enforcing policy for many IT functions. Not involve direct human control. Improve organization’s ability to balance. Availability vs. increasing information’s levels of confidentiality and integrity. Performance Management. Office of Accountability. Dr. Lynne Tingle, Ph.D.. Danielle M. Miller, . M.Ed. , NBCT. Session #305 and Session # 312. Cycle of Continuous Improvement. Strategic Plan 2010 Data Dashboard. Motivation: Image . denoising. How can we reduce noise in a photograph?. Let’s replace each pixel with a . weighted. average of its neighborhood. The weights are called the . filter kernel. What are the weights for the average of a . Agenda. Collaborative Filtering (CF). Pure CF approaches. User-based nearest-neighbor. The Pearson Correlation similarity measure. Memory-based and model-based approaches. Item-based nearest-neighbor. What Is IP Spoofing. Putting a fake IP address in the IP header field for source address (requires root). Why Attackers Spoof?. Hide their identity. Put a blame on someone else. Confuse the defense. CS5670: Intro to Computer Vision. Noah Snavely. Hybrid Images, . Oliva. et al., . http://cvcl.mit.edu/hybridimage.htm. Lecture 1: Images and image filtering. Noah Snavely. Hybrid Images, . Oliva. et al., . Today’s Agenda: TRICARE. Self-Service Options. Today’s Agenda: What Is TRICARE?. What Is TRICARE?: What Is TRICARE?. 4. What. Is TRICARE: TRICARE Stateside Regions. 5. Today’s Agenda: Self-Service Options Online. Henning Lange, Mario . Bergés. , Zico Kolter. Variational Filtering. Statistical Inference. (Expectation Maximization, Variational Inference). Deep Learning. Dynamical Systems. Variational Filtering.