D

deep-learning

Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking

GitHub: https://github.com/ultralytics/ultralytics

https://platform.ultralytics.com

Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.

GitHub: https://github.com/ultralytics/yolov5

https://docs.ultralytics.com/yolov5/

PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export.

GitHub: https://github.com/ultralytics/yolov3

https://docs.ultralytics.com/models/yolov3/

PyTorch sandbox for testing convolutional networks, ResNets, and other architectures on MNIST digits.

GitHub: https://github.com/ultralytics/mnist

https://ultralytics.com

WAVE deep learning for signal readout and reconstruction in full-waveform time-of-flight particle detectors.

GitHub: https://github.com/ultralytics/wave

https://ultralytics.com

Code accompanying the Bitbrain Open Access Sleep (BOAS) dataset: preprocessing, deep learning sleep staging, and technical validation.

IF-Net fork + complete preprocessed ShapeNet archive (tar.xz bundles via git LFS). ShapeNet derivatives: non-commercial research use only.

Classifier to assign label to particle

Fine tunning of a deep neural network (using convolutionnal layers) to reconize a digit from a picture of an handwritten one.

3D Hand Pose Estimation using Multi-View CNNs

✭ MAGNETRON ™ ✭: Detectron2 is a platform for PROXIA that can do POSE ESTIMATION, object detection, segmentation and other visual recognition tasks.

Joule is a dataset uploader/hoster/downloader.

Joule.Host | Documentation

CS 7643 — Spring 2019 Project

Goal: learn more about the underlying deep learning model of GPT2: the Transformer model and, more broadly, the attention mechanism.