Image Classification
Showing 18 of 18 projects
A state-of-the-art PyTorch-based computer vision model for object detection, segmentation, and classification.
A cutting-edge framework for training and deploying state-of-the-art YOLO models for object detection, segmentation, classification, and pose estimation.
A comprehensive collection of PyTorch image models, layers, utilities, and training scripts for computer vision research and applications.
A fast and flexible Python library for image augmentation in computer vision tasks like classification, segmentation, and object detection.
A drop-in replacement for the MNIST dataset, featuring 70,000 Zalando fashion article images for benchmarking machine learning algorithms.
A Python library for building custom machine learning models for tasks like image classification, object detection, and recommendations.
A JavaScript library for client-side NSFW image detection using TensorFlow.js.
A hands-on beginner's guide to machine learning and image classification using Caffe and DIGITS with neural networks.
A web application for training deep learning models with a focus on computer vision tasks.
A browser-based tool that lets anyone create machine learning models without writing code, using TensorFlow.js.
A deep learning framework for training image classification models to solve complex captcha and OCR tasks.
A curated list of deep learning image classification papers and their code implementations since 2014.
A TensorFlow-based CNN solution for recognizing character-based CAPTCHAs, providing training, validation, and API modules.
A deep learning project using Keras to build convolutional and recurrent neural networks for high-accuracy captcha recognition.
A JavaScript application framework for machine learning and its engineering, designed for Web developers.
An open-source deep learning API and server written in C++ that supports multiple backends like PyTorch, TensorRT, and TensorFlow for training and inference.
A lightweight CoreML model for detecting NSFW content in images, specifically trained to distinguish between suggestive and explicit content.
Official repository for Big Transfer (BiT) models, providing pre-trained visual representations for efficient transfer learning across computer vision tasks.
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