Artificial Intelligence Architect at Integration Wizards | NVIDIA Jetson AI Ambassador & Specialist | Speaker | Hackathon Enthusiast

Train fast and accurate computer vision models with NVIDIA’s Transfer Learning Toolkit 3.0; a no-code interface to train and deploy models with TensorRT acceleration.

Photo by Snapwire from Pexels | Logo by NVIDIA

You find yourself staring at your RGB backlit keyboard, with a task at hand and a model to train. You know you need to modify one of your older scripts to use a different network and export a model. …

Build OpenCV with CUDA 11.2 and cuDNN8.1.0 for a faster YOLOv4 DNN inference fps.

Photo by Akash Rai on Unsplash | Detections by author

YOLO, short for You-Only-Look-Once has been undoubtedly one of the best object detectors trained on the COCO dataset. YOLOv4 being the latest iteration has a great accuracy-performance trade-off, establishing itself as one of the State-of-the-art object detectors. Typical mechanisms of employing any object detector in an intelligent video analytics pipeline…

An NVIDIA Deepstream 5.0 and Ryze Tello powered Computer Vision Application to detect wildfires using YOLO.

Image by Author | 10 points if you notice the drone on my shoulder!

Wildfires have been ever-increasing, devouring our planet earth, rendering our planet worse day by day. Just in 2019 and 2020 alone, there has been more than enough wildfires to throw off earth’s ecology out-of-balance. Amazon wildfires, Californian wildfires, Arctic Wildfires and Australian bush-fires are some of the incidents.

Don’t get intimidated by the title of this post, I don’t intend to take over the world with Artificial Intelligence (Debatable, actually). I’m sure most of you remember Skynet, a self-aware Artificially Intelligent agent, back from the Terminator series. Skynet was portrayed in the movie-series to have a sinister idea…

Akash James

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