New York University 4 credits Data Science
Computer Vision is concerned with enabling computers to interpret and understand visual information from the world around us. It has become ubiquitous in our society, with applications in search, image understanding, video surveillance, medical image analysis, drones, self-driving cars, and smart manufacturing. In recent years, developments on deep learning have greatly advanced the performance of various computer vision tasks. The course will start by looking the established area of geometric vision. It will then provide a deep dive into details of neural network based deep learning methods for computer vision and its profound impact on task in recognition, segmentation, and many other vision problems. Prerequisite: CSCI-SHU 101 Introduction to Computer Programming and (CSCI-SHU 360 Marchine Learning or MATH-SHU 235 Probability and Statistic or MATH-SHU 238 Theory of Probability) Fulfillment: CS elective; DS Concentration in AI. Equivalencies: CSCI-UA 480 (Topic must be: Computer Vision)
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