Showing 141-160 of 182 projects
Exploring the capabilities of Graph Neural Networks (GNNs) with Python
A deep learning model for removing watermarks and overlays from images, useful for vibe coders working with AI-generated content.
A comprehensive resource covering machine learning, computer vision, and engineering techniques.
A Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation
R-FCN: Object Detection via Region-based Fully Convolutional Networks - a Matlab library for computer vision tasks.
SincNet is a neural architecture for efficiently processing raw audio samples for speech and audio processing tasks.
PyTorch implementation and explanation of popular graph representation learning papers.
FeatherCNN is a high-performance inference engine for convolutional neural networks.
A real-time emotion recognition library using computer vision and deep learning.
A Python library for spatio-temporal graph convolutional networks, a type of graph neural network for modeling graph-structured data.
A PyTorch library for Deep Graph Convolutional Networks (DeepGCNs) and other graph neural network models.
A comprehensive library for understanding the theory behind digital signal processing, including signals, filtering, and transforms.
DetectoRS is a Python library for object detection using recursive feature pyramid and switchable atrous convolution.
A deep learning library for EEG tasks classification, built with TensorFlow.
A library for studying the robustness of computer vision models to various corruptions and perturbations.
A Python library for predicting depth maps from single RGB images using a fully convolutional residual network (FCRN).
A comprehensive curriculum for learning machine learning and AI development in Python.
A lightweight C++ library for using Keras (TensorFlow) models in edge computing and embedded applications.
A PyTorch-based audio processing library for spectrograms, CQT, and neural network-based preprocessing.
Source code for a research paper exploring the relationship between self-attention and convolutional layers.
Get weekly updates on trending AI coding tools and projects.