Pinned Repositories
LED-defect-detection
Machine vision technology based on artificial intelligence is promoting enterprises to realize intelligent manufacturing. At present, various degrees of LED lamp bead detection are carried out for 20*30mm defects through multi-angle light source technology, and there are certain degrees of defects between good LED lamp beads.
da-fusion
Effective Data Augmentation With Diffusion Models
Efficientnet-Keras
The efficientnet is employed to classify the defects of LCD for 2 or 5 classes
PCB_defect_detection
Project Overview PCB Defect Detection using the ResNet50 model is a machine learning project designed to automatically detect defects in printed circuit boards (PCBs). This project utilizes a deep learning model based on the ResNet50 architecture to classify PCB images as either defective or non-defective.
rCore
Rust version of THU uCore OS. Linux compatible.
diffusion_gen_med
This repository explores diffusion models for medical image data augmentation, crucial for enhancing machine learning model robustness in medical imaging. The four implemented methods include training without augmentation, utilizing keras ImageDataGenerator, employing a DCGAN for image generation, and leveraging DDPM for augmenting images.
DreamDA
DreamDA: Generative Data Augmentation with Diffusion Models (Official Implementation)
hs19991218's Repositories
hs19991218/PCB_defect_detection
Project Overview PCB Defect Detection using the ResNet50 model is a machine learning project designed to automatically detect defects in printed circuit boards (PCBs). This project utilizes a deep learning model based on the ResNet50 architecture to classify PCB images as either defective or non-defective.
hs19991218/rCore
Rust version of THU uCore OS. Linux compatible.