Apprentissage automatique · GitHub

OpenDPD is an end-to-end learning framework built in PyTorch for power amplifier (PA) modeling and digital pre-distortion (DPD). You are cordially invited to contribute to this project by providing your own backbone neural networks, pretrained models or measured PA datasets.

Open source no-code system for text annotation and building of text classifiers

Self‑calibrated neuromorphic hyperspectral imaging pipeline for event cameras with diffractive illumination. Includes end‑to‑end tools for RAW segmentation, multi‑window time‑warping compensation, spectral visualization, and hardware control for synchronized event/frame capture and scanning.

• End-to-end RAW-to-spectrum event processing workflow.
• Auto/manual scan period detection and forward/backward segmentation.

🔬 A Researcher&Agent-Friendly Framework for Time Series Analysis. Train Any Model on Any Dataset!

• Extensibility: Adapt your model/dataset once, train almost any combination of "model" $\times$ "dataset" $\times$ "loss function".
• Compatibility: Accept models with any number/type of arguments in forward; Accept datasets with any number/type of return values in __getitem__; Accept tailored loss calculation for specific models.

🐜🐀🐒🚶 A toolkit for robust markerless 3D pose estimation

IJCAI2020 & IJCV2021 :city_sunrise: Unsupervised Scene Adaptation with Memory Regularization in vivo

Repository of Vision Transformer with Deformable Attention (CVPR2022) and DAT++: Spatially Dynamic Vision Transformerwith Deformable Attention