fbpx
Computer vision and visual AI developers, help guide technology suppliers by taking this 10-minute survey and get $50 off a 2022 Embedded Vision Summit pass and entry in a drawing to win 1 of 50 $25 Amazon gift cards.Learn More & Take The Survey

Ana Salazar, Senior Research Manager at Imagination Technologies, presents the “Challenges and Approaches for Cascaded DNNs: A Case Study of Face Detection for Face Verification” tutorial at the September 2020 Embedded Vision Summit.

This talk explores the challenges of deploying serial computer vision tasks implemented with DNNs. Neural network accelerators have demonstrated significant gains in performance for DNN inference, especially when the net has been quantized. Quantization often brings a loss in accuracy. This loss in accuracy may be considered acceptable in itself but may cause problems if the output of the DNN is used as input for a second DNN which itself has been quantized.

Salazar presents her company’s research into this challenge in the context of a face verification CNN which consumes the output of a face detection CNN, discussing approaches for reducing the impact of quantization in such scenarios.

See here for a PDF of the slides.

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.

Contact

Address

1646 North California Blvd.,
Suite 360
Walnut Creek, CA 94596 USA

Phone
Phone: +1 (925) 954-1411
Scroll to Top