Pinned Repositories
AICity2020_Team_91
nlp-demos
This repository includes Python code and notebooks demonstrating latest natural language processing (NLP) models.
pytorch_uda
PyTorch implementation of Unsupervised Data Augmentation
siosio-rag
This open-source project demonstrates Retrieval Augmented Generation (RAG) using Large Language Models (LLMs).
NTU-P04922004's Repositories
NTU-P04922004/AICity2020_Team_91
NTU-P04922004/nlp-demos
This repository includes Python code and notebooks demonstrating latest natural language processing (NLP) models.
NTU-P04922004/pytorch_uda
PyTorch implementation of Unsupervised Data Augmentation
NTU-P04922004/siosio-rag
This open-source project demonstrates Retrieval Augmented Generation (RAG) using Large Language Models (LLMs).
NTU-P04922004/avatarify-python
Avatars for Zoom, Skype and other video-conferencing apps.
NTU-P04922004/awesome_LLMs_interview_notes
LLMs interview notes and answers:该仓库主要记录大模型（LLMs）算法工程师相关的面试题和参考答案
NTU-P04922004/batch-bg-remover-photoshop
This script will automatically detect background of a photo and remove the background. This uses a new feature of photoshop cc 2020.
NTU-P04922004/DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
NTU-P04922004/handtracking
Building a Real-time Hand-Detector using Neural Networks (SSD) on Tensorflow
NTU-P04922004/HeadHunter
Code for the head detector (HeadHunter) proposed in our CVPR 2021 paper Tracking Pedestrian Heads in Dense Crowd.
NTU-P04922004/HeadHunter--T
This repository is the official implementation of HeadHunter-T, the head tracker discussed in the CVPR paper, mentioned herewith.
NTU-P04922004/open-images-2019-instance-segmentation
7th place solution to the Open Images 2019 Instance Segmentation competition
NTU-P04922004/PaletteSelection
Automatic Color Palette Selection (Python)
NTU-P04922004/SODsurvey
Salient Object Detection in the Deep Learning Era: An In-Depth Survey