Learn about the methodology and tools for AI-driven arc fault detection to create real-time classification on MCUs, improving accuracy and reducing false trips, for edge deployment. Learn how embedded ...

This repo provides a clean implementation of YoloV3 in TensorFlow 2.0 using all the best practices. I have created a complete tutorial on how to train from scratch ...

The last few years have seen a rise in novel differentiable graphics layers which can be inserted in neural network architectures. From spatial transformers to differentiable graphics renderers, these ...

TensorFlow is an open-source machine learning framework developed by Google for numerical computation and building mach TensorFlow ops like tf.cond and tf.while_loop continue to work, but control flow ...

Python libraries are pre-written collections of code designed to simplify programming by providing ready-made functions for specific tasks. They eliminate the need to write repetitive code and cover ...

Developing intelligent neuromorphic solutions remains a challenging endeavor. It requires a solid conceptual understanding of the hardware's fundamental building blocks. Beyond this, accessible and ...

Graph neural networks have been shown to achieve excellent performance for several crucial tasks in particle physics, such as charged particle tracking, jet tagging, and clustering. An important ...