a collection of computer vision projects&tools. 计算机视觉方向项目和工具集合。

This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.

Demonstrates knowledge distillation for image-based models in Keras.

This repository shows how to train a custom detection model with the TFOD API, optimize it with TFLite, and perform inference with the optimized model.

A curated collection of AI, data engineering, and DevOps projects featuring real-world applications, advanced techniques, and tutorials—ideal for learners and practitioners exploring data science and machine learning.

Code of the ICASSP 2022 paper "Gradient Variance Loss for Structure Enhanced Super-Resolution"

Developed a churn prediction model using XGBoost, with comprehensive data preprocessing and hyperparameter tuning. Applied SHAP for feature importance analysis, leading to actionable business insights for targeted customer retention.

本仓库包含了完整的深度学习应用开发流程，以经典的手写字符识别为例，基于LeNet网络构建。推理部分使用torch、onnxruntime以及openvino框架💖

Automated Shorthand Recognition using Optimized DNNs

Leverage the Intel® Distribution of OpenVINO™ Toolkit to fast-track development of high-performance computer vision and deep learning inference applications, and run pre-trained deep learning models for computer vision on-premise.

ptdeco is a library for model optimization by matrix decomposition built on top of PyTorch

DA2Lite is an automated model compression toolkit for PyTorch.

Vision-lanugage model example code.

Minimal Reproducibility Study of (https://arxiv.org/abs/1911.05248). Experiments with Compression of Deep Neural Networks

A deep learning framework that implements Early Exit strategies in Convolutional Neural Networks (CNNs) using Deep Q-Learning (DQN). This project enhances computational efficiency by dynamically determining the optimal exit point in a neural network for image classification tasks on CIFAR-10.

quantization example for pqt & qat

This repository includes code for the paper "Towards Zero Touch Networks: Cross-Layer Automated Security Solutions for 6G Wireless Networks" published in IEEE TCOM, focusing on autonomous cybersecurity (physical-layer authentication and cross-layer intrusion detection) using AutoML techniques.

Successfully established a clustering model which can categorize the customers of a renowned Indian bank into several distinct groups, based on their behavior patterns and demographic details.

Enhanced BR2804-1700KV Motor Field Oriented Control with a Tiny Neural Network

compares different pretrained object classification with per-layer and per-channel quantization using pytorch