Hoseong Lee hoya012

Deep Learning Research Engineer

Achievements

hoya012/README.md

Received the B.S. degrees, in Electrical and Computer Engineering from Seoul National University, Seoul, Korea, in 2016.
Received the M.S. degrees, in Electrical and Computer Engineering from Seoul National University, Seoul, Korea, in 2018.
Joined the SUALAB. ,Seoul, Korea, as aDeep Learning Research Engineer, in 2018.
SUALAB was acquired by Cognex in 2019.10. So, I am currently working at Cognex.

Image Recognition using Deep Learning
- Classification
- Object Detection
- Semantic Segmentation
- Labeling Noise Detection
Anomaly Detection
- Out-of-distritubion Detection
- Defect Generation
Image Processing using Deep Learning
- Super Resolution
- Style Transfer
- Image Denoising
- Image Matching
Learning Theory
- Weakly-Supervised Learning
- Semi-Supervised Learning
- Self-Supervised Learning
AI Conference Paper Reading

deep_learning_object_detectiondeep_learning_object_detectionPublic
A paper list of object detection using deep learning.
Python 11.4k 2.8k
awesome-anomaly-detectionawesome-anomaly-detectionPublic
A curated list of awesome anomaly detection resources
2.8k 513
carrier-of-tricks-for-classification-pytorchcarrier-of-tricks-for-classification-pytorchPublic
carrier of tricks for image classification tutorials using pytorch.
Python 103 21
automatic-mixed-precision-tutorials-pytorchautomatic-mixed-precision-tutorials-pytorchPublic
Automatic Mixed Precision Tutorials using pytorch. Based on PyTorch 1.6 Official Features, implement classification codebase using custom dataset.
Python 89 7
semantic-segmentation-tutorial-pytorchsemantic-segmentation-tutorial-pytorchPublic
A simple PyTorch codebase for semantic segmentation using Cityscapes.
Jupyter Notebook 195 39
swa-tutorials-pytorchswa-tutorials-pytorchPublic
Stochastic Weight Averaging Tutorials using pytorch.
Python 33 4