(video) The Basics of Building a Deep Learning Model | Brodmann17’s Deep Learning 101 Series

Curious about how vision perception software works in #ADAS? Ever wondered what a Neural Network is or what computer vision engineers mean by ‘training a model’? Then this playlist is for you. It’s presented by Brodmann17’s Co-founder Dr. Amir Alush, an expert in Deep Learning, who introduces you to the building blocks of what our award-wining products are based on – patented Deep Learning technology.

Dr Amir Alush is an enthusiast for algorithms coding and design. He has many years experience in designing and implementing algorithms in the fields of Computer Vision, Machine Learning and Deep Learning working on big-data. His research for his Phd focused on Machine Learning algorithms and discrete optimization problems with applications for Computer Vision. His own personal breakthroughs in Deep Learning culminated in him co-founding Brodmann17 to bring uncompromising AI to the edge and everyday applications.

Brodmann17 develops camera-first ADAS that is revolutionizing safety in mobility. The company’s computer-vision-centered technology saves 95% of compute power. This huge saving in cost has brought AI for the very first time to new verticals including mass-market passenger vehicles, video telematics and micro mobility.

Brodmann17’s AI is based on deep learning neural networks that extract all possible information from a video to make the entire ADAS software smarter. Brodmann17’s patented perception software is hardware agnostic and highly scalable. It is easy to integrate and deploy as it can work on any processor from low-power edge to the cloud.

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