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Lecture Date: October 15, 2019
Chapter: Gujarat
Chapter Chair: Suman Mitra
Topic: Signal Processing for Neural Prostheses
Lecture Date: August 5, 2019
Chapter: Gujarat
Chapter Chair: Suman Mitra
Topic: Sensing Technologies and Applications in Smart Lighting and Beyond
Lecture Date: July 23-24, 2019
Chapter: Hyderabad
Chapter Chair: Lalitha Vadlamani
Topic: Machine Learning in Connected Lighting: Applications and Opportunities
The ELIOT project aims to study communication networks of interconnected devices that lie at the core of many key future technologies such as distributed control systems for autonomous vehicles, sensor networks for structural health monitoring and for smart cities. In addition to reliability, all these applications come with strict requirements in terms of: energy efficiency, security, latency and self-optimization capabilities, and demand for innovative enabling technologies. The
January 18-22, 2021
NOTE: Location changed to--Virtual Conference
September 21-23, 2020
NOTE: Location changed to--Virtual Conference
Amazon AI has open positions in Palo Alto, California, for applied scientists (both interns and full time)
in all areas of human language technology, with special focus on Deep Learning (DL) models for
speech recognition, machine translation and text-to-speech.
The saliency detection technologies are very useful to analyze and extract important information from given multimedia data, and have already been extensively used in many multimedia applications. Past studies have revealed that utilizing the global cues is effective in saliency detection. Nevertheless, most of prior works mainly considered the single-scale segmentation when the global cues are employed. In this paper, we attempt to incorporate the multi-scale global cues for saliency detection problem.
With the development of video coding technology, high-efficiency video coding (HEVC) has become a promising alternative, compared with the previous coding standards, for example, H.264. In general, H.264 to HEVC transcoding can be accomplished by fully H.264 decoding and fully HEVC encoding, which suffers from considerable time consumption on the brute-force search of the HEVC coding tree unit (CTU) partition for rate-distortion optimization (RDO).