The Intel-OpenVINO Toolkit provides many great functionalities for Deep-Learning model optimization, inference and deployment. Perhaps the most interesting and practical tool among them is the ...
Traditionally, Deep-Learning models are trained on high-end GPUs. But for inference, Intel CPUs and edge devices like NVidia’s Jetson and Intel-Movidius VPUs are preferred. Most of these Intel CPUs ...
Deep Learning models inferencing on video stream inputs in computer vision applications are mostly used for object detection, image segmentation, and image classification. In many cases, we fail to ...
The training of neural-network architectures is what drives most of us who are involved in the field of Deep Learning. We fixate endlessly over the amount of data, its quality, and what neural network ...
In this post, we will learn how to squeeze the maximum performance out of OpenCV's Deep Neural Network (DNN) module using Intel's OpenVINO toolkitpost, we compared the performance of OpenCV and other ...
In this post, we will learn the pros and cons of using Face Recognition as an authentication method. We will also see how it can be spoofed and the methods that can be used to detect the spoofing ...
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In 2007, right after finishing my Ph.D., I co-founded TAAZ Inc. with my advisor Dr. David Kriegman and Kevin Barnes. The scalability, and robustness of our computer vision and machine learning algorithms have been put to rigorous test by more than 100M users who have tried our products.
