201 - 210 of 217 results for: CS

(Formerly CS323) The field of computer vision has seen an explosive growth in past decade. Much of recent effort in vision research is towards developing algorithms that can perform high-level visual recognization tasks on real-world images and videos. With development of Internet, this task becomes particularly challenging and interesting given the heterogeneous data on the web. Course will focus on reading recent research papers that are focused on solving high-level visual recognition problems, such as object recognition and categorization, scene understanding, human motion understanding, etc. Project required. Prerequisite: some experience in research with one of the following fields: computer vision, image processing, computer graphics, machine learning.

The course surveys recent developments in high level and 3D computer vision and will focus on reading recent research papers on topics related to 3D object recognition and representation, spatial inference, activity understanding, human vision and 3D perception. The course is inspired by a famous series of workshops (called 3d-RR) which have been offered during the International Conference in Computer Vision (ICCV) since 2007. Prerequisites - Some experience in research with one of the following fields: computer vision, image processing, computer graphics, machine learning.

High-performance embedded system design. Student teams of two software engineers (C experience required) and one hardward engineer (Verilog experience required) build a fully functioning Internet router Work in teams of three. How router interoperates with others in class. Open-ended design challenge judged by panel of industry experts. Prerequisites: CS 144, 244, or network programming experience.

Networking research in wireless systems. Topics include: multi-channel/multi-radio systems, routing, coding, physical layer hints, low power, mesh networking, interference cancellation, technological trends, and protocol design. Students implement and test research ideas on SWAN, a WiFi testbed.

Discussion of research publications that are of current interest in distributed systems. Students are expected to read all papers, and sign up for presentation of one paper. The course itself is 1 unit. Those interested in working on a project along with the readings should enroll for 3 units.

Advanced data structures: union-find, self-adjusting data structures and amortized analysis, dynamic trees, Fibonacci heaps, universal hash function and sparse hash tables, persistent data structures. Advanced combinatorial algorithms: algebraic (matrix and polynomial) algorithms, number theoretic algorithms, group theoretic algorithms and graph isomorphism, online algorithms and competitive analysis, strings and pattern matching, heuristic and probabilistic analysis (TSP, satisfiability, cliques, colorings), local search algorithms. May be repeated for credit. Prerequisite: 161 or 261, or equivalent.

Topics: fundamental techniques used in the development of exact and approximate algorithms for combinational optimization problems such as generalized flow, multicommodity flow, sparsest cuts, generalized Steiner trees, load balancing, and scheduling. Using linear programming, emphasis is on LP duality for design and analysis of approximation algorithms; interior point methods for LP. Techniques for development of strongly polynomial algorithms. Prerequisites: 161 or 261, or equivalent.

Topics at the interface of computer science and game theory such as: algorithmic mechanism design; combinatorial auctions; computation of Nash equilibria and relevant complexity theory; congestion and potential games; cost sharing; game theory and the Internet; matching markets; network formation; online learning algorithms; price of anarchy; prior-free auctions; selfish routing; sponsored search. Prerequisites: 154N and 161, or equivalents.

With devices like Pebble and Google Glass moving from labs to consumer use, Wearable Computing represents the forefront of HCI innovation. In this course, students will engage with a broad range of issues around the design and development of wearable devices and systems and develop their own wearable interaction. The course begins with use, analysis, and redesign of an existing wearable, followed by a larger group project integrating concepts from the course to prototype a novel wearable interaction. Students work in project teams, prototyping their wearable concept and communicating their progress through demonstration, final report, and presentation. Google Glass will be available for students interested in experimenting with this platform. Prerequisites: One of the following: CS 147 or CS 247.