Caffe is a deep learning framework developed by the Berkeley Vision and Learning Center (BVLC) and one of the most popular community frameworks for image recognition. Caffe is often used as a benchmark together with AlexNet*, a neural network topology for image recognition, and ImageNet*, a database of labeled images.
This paper demonstrates a special version of Caffe* — a deep learning framework originally developed by the Berkeley Vision and Learning Center (BVLC) — that is optimized for Intel® architecture.
Don't get me wrong, I was a quite willing participant with all of this.
This article presents a performance test of Intel® tuning platform composed by Intel® processor, Intel® C++ Compiler XE and Intel® Math Kernel Library (Intel® MKL) applied to usual AI problems, with two existing approaches of artificial intelligence probed.
Learn to build a face access control solution, get horrified in a haunted high school, and be sure to register for the Intel® HPC Developer Conference this month.
Announcing new IoT developer kits this month along with tips on which processor is right for your VR projects.
At the Autodesk University event in Las Vegas, November 14-16, civil and commercial/industrial designers and manufacturers who use Autodesk software came together to see The Future of Making Things.
This month we introduce our newest VR newsletter deVR Beat; link to the keynotes from the Intel® HPC Developer Conference,meet the winners of the Intel® Modern Code Challenge and more.
This month we add persistent memory to our line-up. Read more about image classification, visualization and fly with the latest VR wingsuit!