Diffusion probabilistic models are an exciting new area of research showing great promise in image generation. In retrospect, diffusion-based generative models were first introduced in 2015 and ...
Recent advances in AI-based Image Generation spearheaded by Diffusion models such as Glide, Dalle-2, Imagen, and Stable Diffusion have taken the world of “AI Art generation" by storm. Generating ...
DeepLab models, first debuted in ICLR ‘14, are a series of deep learning architectures designed to tackle the problem of semantic segmentation. After making iterative refinements through the years, ...
In recent years, we have seen tremendous progress in the YOLO series, now hosting both anchor-free and anchor-based object detection models. Instead of focusing solely on architectural changes, YoloR ...
According to CDC, "An estimated 1 in 25 adult drivers (18 years or older) report falling asleep while driving…". The article reports, “...drowsy driving was responsible for 91,000 road accidents…”. To ...
Document Scanning is a background segmentation problem that can be solved using various methods. It is one of the extensively used applications of computer vision. In this article, we are considering ...
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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.
