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The good generalization performance of conventional pattern classifiers often relies on the size of training data labeled by costly human labor. These days, publicly available web resources grow explosively, and this allows us to easily obtain abundant and cheap web data. Yet, web data are usually not as cooperative as human labeled data. In this paper, we explore the use of web text data to aid image classification.
To improve the parallel processing capability of video coding, the emerging high efficiency video coding (HEVC) standard introduces two parallel techniques, i.e., Wavefront Parallel Processing (WPP) and Tiles , to make it much more parallel-friendly than its predecessors. However, these two techniques are designed to explore coarse-grained parallelism in HEVC encoding on multicore Central Processing Unit (CPU) platforms.
Lecture Date: February 10, 2020
Chapter: Italy
Chapter Chair: Mauro Barni
Topic: Accessing from the sky: UAV challenges from a
communication and signal processing perspective
Accounts for ordering membership development materials are now created at the Section and Student Branch level. New sign in credentials for the Marcore ordering portal were sent to MD Chairs (or Section Chairs) and Student Branch Chairs in early August.
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Accounts for ordering membership development materials are now created at the Section and Student Branch level. New sign in credentials for the Marcore ordering portal were sent to MD Chairs (or Section Chairs) and Student Branch Chairs in early August.
Lecture Date: December 17, 2019
Chapter: Poland
Chapter Chair: Piotr Augustyniak
Topic: Towards Autonomous Video Surveillance
AGH University of Science and Technology, Department of
Computer Science, Kraków, Poland
Lecture Date: December 19, 2019
Chapter: Poland
Chapter Chair: Piotr Augustyniak
Topic: Privacy-Preserving Localization and Recognition of Human Activities
University of Rzeszów, Institute of Computer Science, Rzeszów, Poland
This webinar, “Toward Efficient and Flexible CNN-based Denoising in Photography,” begins with the design of denoising CNN (DnCNN) model by incorporating residual learning and batch normalization.
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The IEEE Signal Processing Society is dedicated to supporting the professional growth and career advancement of its members in the dynamic field of signal processing. Learn More
Signal processing education and professional development program for all career levels. Learn more.