Andrew Tao – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2023-04-04T17:01:27Z http://www.open-lab.net/blog/feed/ Andrew Tao <![CDATA[Improving Computer Vision with NVIDIA A100 GPUs]]> http://www.open-lab.net/blog/?p=18363 2023-04-04T17:01:27Z 2020-06-16T17:23:00Z During the 2020 NVIDIA GPU Technology Conference keynote address, NVIDIA founder and CEO Jensen Huang introduced the new NVIDIA A100 GPU based on the NVIDIA...]]>

During the 2020 NVIDIA GPU Technology Conference keynote address, NVIDIA founder and CEO Jensen Huang introduced the new NVIDIA A100 GPU based on the NVIDIA Ampere GPU architecture. In this post, we detail the exciting new features of the A100 that make NVIDIA GPUs an ever-better powerhouse for computer vision workloads. We also showcase two recent CV research projects from NVIDIA Research…

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Andrew Tao <![CDATA[Using Multi-Scale Attention for Semantic Segmentation]]> http://www.open-lab.net/blog/?p=17964 2023-02-13T17:38:33Z 2020-06-12T17:40:00Z There��s an important technology that is commonly used in autonomous driving, medical imaging, and even Zoom virtual backgrounds: semantic segmentation....]]>

There’s an important technology that is commonly used in autonomous driving, medical imaging, and even Zoom virtual backgrounds: semantic segmentation. That’s the process of labelling pixels in an image as belonging to one of N classes (N being any number of classes), where the classes can be things like cars, roads, people, or trees. In the case of medical images, classes correspond to different…

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Andrew Tao <![CDATA[DetectNet: Deep Neural Network for Object Detection in DIGITS]]> http://www.open-lab.net/blog/parallelforall/?p=6911 2022-08-21T23:37:55Z 2016-08-11T07:01:49Z The NVIDIA Deep Learning GPU Training System (DIGITS) puts the power of deep learning in the hands of data scientists and researchers. Using DIGITS you can...]]>

The NVIDIA Deep Learning GPU Training System (DIGITS) puts the power of deep learning in the hands of data scientists and researchers. Using DIGITS you can perform common deep learning tasks such as managing data, defining networks, training several models in parallel, monitoring training performance in real time, and choosing the best model from the results browser.

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