Flyer

Flyer

Video analytics involves processing video content in real-time, extracting metadata, sending out alerts, and delivering actionable intelligence insights to security staff or other systems. Video analytics products apply artificial intelligence to cameras to recognize temporal and spatial events. Video analytics are needed in various end applications such as quality inspection, industrial process automation, and workplace security. It is crucial to have video analytics performed at the edge on the multiple streams from on-premises cameras to make automated predictions with high accuracy and low latency. This talk explains the co-design of hardware friendly algorithms and corresponding domain specific accelerator architectures for machine learning inference at the edge for video analytics.

Monday evening, October 30 virtual

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Thanks,

Mr. Mesecher & Dr. Donaldson
Signal Processing Vice Chair & Chair, 2023
IEEE LI Section
Website

Accurate image segmentation holds significance for vital clinical applications such as diagnosis and surgery planning. While deep neural networks have excelled in achieving superior segmentation outcomes via fully supervised learning, their reliance on substantial annotated training data is a challenge. Procuring extensive labeled datasets for medical images is labor-intensive and costly due to the need for clinical expertise in annotations. Thus, an opportunity for improvement is evident. Hence, the critical need to devise strategies for attaining medical images with scant annotations while harnessing untapped potential within unlabeled data during training. We harness the power of self-supervised representation learning and semi-supervised learning in this regard and perform extensive experiments on images from multiple modalities:  Computer Tomograhpy (CT) scan, Magnetic Resonance Imaging (MRI) scan, Histopathology studies, etc. Our recent research showcases that even with minimal annotations estimate of x<10%, we achieve comparable or superior performance compared to fully supervised approaches.

Friday evening, August 25 virtual

Register

Thanks,

Mr. Mesecher & Dr. Donaldson
Signal Processing Vice Chair & Chair, 2023
IEEE LI Section
Website

The last decade has witnessed rapid progress in science and technology and several breakthroughs that have resulted in the shifting of the human-technology frontier. The global pandemic generated a large perturbation with long term implications in both technological and societal realms. In this context, I argue that engineering careers should include not only technical fields but also science and technology management and administration, education, communication, ethics, and policy/diplomacy at local, national, and international levels. Adopting such a broad viewpoint will open many interesting and highly satisfactory career paths for our community and may bring personal and professional fulfillment in unexpected ways.

Wednesday Evening, June 21 virtual

Register

Thanks,

Mr. Mesecher & Dr. Donaldson
Signal Processing Vice Chair & Chair, 2023
IEEE LI Section
Website

Thursday evening, December 15 virtual

Register

Thanks,

Mr. Mesecher & Dr. Donaldson
Signal Processing Vice Chair & Chair, 2022
IEEE LI Section
Website

Wednesday afternoon, November 30 virtual

Register

Thanks,

Mr. Mesecher & Dr. Donaldson
Signal Processing Vice Chair & Chair, 2022
IEEE LI Section
Website