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Châu Thế Hân's Projects

annotated_deep_learning_paper_implementations icon annotated_deep_learning_paper_implementations

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

aster icon aster

Recognizing cropped text in natural images.

awesome-face_recognition icon awesome-face_recognition

papers about Face Detection; Face Alignment; Face Recognition && Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution && Face Deblurring; Face Generation && Face Synthesis; Face Transfer; Face Anti-Spoofing; Face Retrieval;

craft-pytorch icon craft-pytorch

Official implementation of Character Region Awareness for Text Detection (CRAFT)

cream icon cream

This is a collection of our NAS and Vision Transformer work.

crnn icon crnn

Convolutional Recurrent Neural Network (CRNN) for image-based sequence recognition.

crnn-keras icon crnn-keras

CRNN (CNN+RNN) for OCR using Keras / License Plate Recognition

cs231n_2016 icon cs231n_2016

CS231n Convolutional Neural Networks for Visual Recognition

ctc-ocr icon ctc-ocr

A TensorFlow implementation of hybird CNN-LSTM model with CTC loss for OCR problem

deep-learning-books icon deep-learning-books

Books for machine learning, deep learning, math, NLP, CV, RL, etc. 一些机器学习、深度学习等相关话题的书籍。

deeplearning-500-questions icon 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[email protected] 版权所有,违权必究 Tan 2018.06

fire-detection-cnn icon fire-detection-cnn

real-time fire detection in video imagery using a convolutonal neural network (deep learning) - from our ICIP 2018 paper (Dunnings / Breckon)

fire-detection-image-dataset icon fire-detection-image-dataset

This dataset contains normal images and images with fire. It is highly unbalanced to reciprocate real world situations. It consists of a variety of scenarios and different fire situations (intensity, luminosity, size, environment etc).

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