A neural network that transforms a design mock-up into a static website.

Simple Binary Encoding (SBE) - High Performance Message Codec

Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

🔥🔥🔥自定义Android相机(仿抖音 TikTok)，其中功能包括视频人脸识别贴纸，分段录制，视频裁剪，视频帧处理，获取视频关键帧，视频旋转，添加滤镜，添加水印，合成Gif到视频，文字转视频，图片转视频，音视频合成，音频变声处理，SoundTouch，Fmod音频处理。 Android camera(imitation Tik Tok), which includes video editor,audio editor,video face recognition stickers, segment recording,video cropping, video frame processing, get the first video frame, key frame, video rotation, add filter Mirror ,add watermark ,add gif to video, add text to video, picture to video, audio and video synthesis, audio change processing, SoundTouch, Fmod audio processing.

Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning

Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet

最新版ffmpeg3.3-android，并通过CMake方式移植到Android中,并实现编解码，转码，推拉流，滤镜等各种功能

Tensorflow seq2seq Implementation of Text Summarization.

An open-source tool for sequence learning in NLP built on TensorFlow.

Sequence to sequence learning using TensorFlow.

This repository contains my full work and notes on Coursera's NLP Specialization (Natural Language Processing) taught by the instructor Younes Bensouda Mourri and Łukasz Kaiser offered by deeplearning.ai

BERT for Multitask Learning

Conversation models in TensorFlow. (website removed)

Multiple implementations for abstractive text summurization , using google colab

FFmpegCommand适用于Android的FFmpeg命令库，实现了对音视频相关的处理，能够快速的处理音视频，大概功能包括：音视频剪切，音视频转码，音视频解码原始数据，音视频编码，视频转图片或gif，视频添加水印，多画面拼接，音频混音，视频亮度和对比度，音频淡入和淡出效果等

slot filling, intent detection, joint training, ATIS & SNIPS datasets, the Facebook’s multilingual dataset, MIT corpus, E-commerce Shopping Assistant (ECSA) dataset, CoNLL2003 NER, ELMo, BERT, XLNet

Four styles of encoder decoder model by Python, Theano, Keras and Seq2Seq

Implementation of a seq2seq model for Speech Recognition using the latest version of TensorFlow. Architecture similar to Listen, Attend and Spell.

Code for our paper "Multi-scale Guided Attention for Medical Image Segmentation"

Implementation of a seq2seq model for summarization of textual data. Demonstrated on amazon reviews, github issues and news articles.

Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling" (https://arxiv.org/abs/1609.01454)

News summarization using sequence to sequence model with attention in TensorFlow.

Decode All Bases - Base Scheme Decoder

Implementation of abstractive summarization using LSTM in the encoder-decoder architecture with local attention.

Demo code of the paper: "Deep Image Harmonization", Y.-H. Tsai, X. Shen, Z. Lin, K. Sunkavalli, X. Lu and M.-H. Yang, CVPR 2017

A fast Go Avro codec

This is an ongoing re-implementation of DeepLab_v3_plus on pytorch which is trained on VOC2012 and use ResNet101 for backbone.

Seq2SeqSharp is a tensor based fast & flexible encoder-decoder deep neural network framework written by .NET (C#). It has many highlighted features, such as automatic differentiation, many different types of encoders/decoders(Transformer, LSTM, BiLSTM and so on), multi-GPUs supported and so on.