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Jeong-Hoe Ku's Projects

structure_knowledge_distillation icon structure_knowledge_distillation

The official code for the paper 'Structured Knowledge Distillation for Semantic Segmentation'. (CVPR 2019 ORAL) and extension to other tasks.

stylegan icon stylegan

StyleGAN - Official TensorFlow Implementation

swin-transformer icon swin-transformer

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

tensorflow icon tensorflow

Computation using data flow graphs for scalable machine learning

tensorflow-tutorials icon tensorflow-tutorials

텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다

tensorpack icon tensorpack

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

tf-imagenet icon tf-imagenet

TensorFlow ImageNet - Training and SOTA checkpoints

thingsboard icon thingsboard

Open-source IoT Platform - Device management, data collection, processing and visualization.

tpu icon tpu

Reference models and tools for Cloud TPUs.

transformer-from-scratch icon transformer-from-scratch

Well documented, unit tested, type checked and formatted implementation of a vanilla transformer - for educational purposes.

transformers icon transformers

🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.

tresnet icon tresnet

TResNet: High Performance GPU-Dedicated Architecture

up-detr icon up-detr

[CVPR2021 Oral] UP-DETR: Unsupervised Pre-training for Object Detection with Transformers

vitdet icon vitdet

Unofficial implementation of Exploring Plain Vision Transformer Backbones for Object Detection

vscode-tools-for-ai icon vscode-tools-for-ai

VS Code Tools for AI is an extension to build, test, and deploy Deep Learning / AI solutions. It seamlessly integrates with Azure Machine Learning for robust experimentation capabilities, including but not limited to submitting data preparation and model training jobs transparently to different compute targets. Additionally, it provides support for custom metrics and run history tracking, enabling data science reproducibility and auditing. Enterprise ready collaboration, allow to securely work on project with other people.

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