The convertor/conversion of deep learning models for different deep learning frameworks/softwares.
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Updated
Jun 26, 2023
The convertor/conversion of deep learning models for different deep learning frameworks/softwares.
A clear, concise, simple yet powerful and efficient API for deep learning.
Infrastructures™ for Machine Learning Training/Inference in Production.
A lightweight deep learning library
One-Stop System for Machine Learning.
Deep Learning Library. For education. Based on pure Numpy. Support CNN, RNN, LSTM, GRU etc.
A deep learning framework created from scratch with Python and NumPy
benchmark for embededded-ai deep learning inference engines, such as NCNN / TNN / MNN / TensorFlow Lite etc.
[Experimental] Graph and Tensor Abstraction for Deep Learning all in Common Lisp
以jax为后端的类似keras的框架
[MICCAI'24] Official implementation of "BGF-YOLO: Enhanced YOLOv8 with Multiscale Attentional Feature Fusion for Brain Tumor Detection".
implementation of WSAE-LSTM model as defined by Bao, Yue, Rao (2017)
[CVPR 2024] CFAT: Unleashing Triangular Windows for Image Super-resolution
NumPy实现类PyTorch的动态计算图和神经网络框架(MLP, CNN, RNN, Transformer)
A visual Deep Learning Framework for the Web - Built with WebGPU, Next.js and ReactFlow.
[IMAVIS] Official implementation of "ASF-YOLO: A Novel YOLO Model with Attentional Scale Sequence Fusion for Cell Instance Segmentation".
Deep Learning framework in C++/CUDA that supports symbolic/automatic differentiation, dynamic computation graphs, tensor/matrix operations accelerated by GPU and implementations of various state-of-the-art graph neural networks and other Machine Learning models including Covariant Compositional Networks For Learning Graphs [Risi et al]
Explore the latest AI Agent Framework!
Flow-based data pre-processing for deep learning
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