Popular GitHub Repositories for Fls Fusion Net

PyTorch implementation of the U-Net for image semantic segmentation with high quality images

The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."

.NET API Gateway

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility

A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.

Samples for ML.NET, an open source and cross-platform machine learning framework for .NET.

The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"

Text recognition (optical character recognition) with deep learning methods, ICCV 2019

A Tensorflow implementation of CapsNet(Capsules Net) in paper Dynamic Routing Between Capsules

A C#/.NET library to run LLM (?LLaMA/LLaVA) on your local device efficiently.

.NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C# and F#.

.NET, Angular, Clean Architecture, Clean Code, SOLID Principles, KISS Principle, DRY Principle, Fail Fast Principle, Common Closure Principle, Common Reuse Principle, Acyclic Dependencies Principle, Mediator Pattern, Result Pattern, Folder-by-Feature Structure, Separation of Concerns

TensorFlow API for .NET languages

mean Average Precision - This code evaluates the performance of your neural net for object recognition.

AI Multi-Agent Framework in .NET

[ICRA'23] BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation

This is the repo for our new project Highly Accurate Dichotomous Image Segmentation

3D U-Net model for volumetric semantic segmentation written in pytorch

micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape