Neural Network Compression Framework for enhanced OpenVINO™ inference
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Updated
May 28, 2025 - Python
Neural Network Compression Framework for enhanced OpenVINO™ inference
Implementation of our Pattern Recognition paper "DMT: Dynamic Mutual Training for Semi-Supervised Learning"
A Natural Language Inference (NLI) model based on Transformers (BERT and ALBERT)
This repository containts the pytorch scripts to train mixed-precision networks for microcontroller deployment, based on the memory contraints of the target device.
A pytorch helper library for Mixed Precision Training, Initialization, Metrics and More Utilities to simplify training of deep learning models
Let's train CIFAR 10 Pytorch with Half-Precision!
Using Deep Learning To Identify And Classify Building Damage
Code repository for "Reducing Underflow in Mixed Precision Training by Gradient Scaling" presented at IJCAI '20
Pytorch implementation of the paper Mixed Precision DNNs: All you need is a good parametrization.
Steel Defect Detection using U-Net. Optimising training and inference using Automatic Mixed Precision and TensorRT respectively.
[CVPR 2015] FaceNet: A Unified Embedding for Face Recognition and Clustering
demo for pytorch-distributed
A Python package for simulating low precision arithmetic in scientific computing and machine learning
A Tiny Version of the Original ultralytics/yolov5
[TMLR, 2024] Modular Quantization-Aware Training for 6D Object Pose Estimation
This repository contains the code and reports for the course INFR11132 Machine Learning Practical. Overall Mark Achieved - 75%
This project implements a neural network-based chess AI using TensorFlow and Keras. The model uses convolutional layers and residual blocks to predict the best chess moves and evaluate board states. It combines policy and value predictions to create a robust chess-playing AI, inspired by AlphaZero's architecture.
YOLOv12 Underwater Object Detection is an open-source suite for underwater object detection, built on YOLOv12. It offers an end-to-end pipeline with GPU-accelerated training, customizable data augmentations, real-time inference via Gradio, and support for model export (ONNX & PyTorch).
A food vision app is an image classification app for 101 dishes demonstrating the power of transfer learning
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