Deep learning for vision processing: In-depth design techniques

Convolutional neural networks (CNNs) and other deep learning techniques are one of the hottest topics in computer vision today, as you can tell by the number of columns I’ve devoted to the subject. Most recently, I discussed three talks from May’s Embedded Vision Summit, all of which covered processors for deep learning, each delving into a different co-processor type: GPUs, FPGAs, and DSPs. Today, I’d like to delve into more detail, showcasing videos and an article that provide in-depth implementation tips once you’ve made your processor architecture selection. And for those who want a hands-on technical introduction to deep learning for computer vision, see the information about an upcoming live tutorial at the end of the article. It includes a special discount code for VSD readers. The first presentation, “Semantic…


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