fendaq Goto Github PK

latex_ocr

:gem: 数学公式识别

latticelstm

Chinese NER using Lattice LSTM. Code for ACL 2018 paper.

law

law_pre_baseline

baseline for law_pre

lawcompetition

this is for a competition in ;aw

layer-recurrent-neural-networks-lrnn-tf

Layer Recurrent Neural Network-LRNN-tensorflow-tf

ld-net

Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling

leaflet-image-hotspots

热点图像区域编辑功能的实现，能够在图片上绘制、编辑、删除图形区域以及文字说明

leam

learn-nginx

学习nginx配置, 包括: 编译安装、反向代理、重定向、url重写、nginx缓存、跨域配置等

learning-opencv-3_examples

learning-rate

Implementation of Learning Rate Finder, SGDR and Cyclical Learning Rate in Keras

learning-to-see-in-the-dark

Learning to See in the Dark. CVPR 2018

learningtocompare-pytorch

Pytorch Implementation for CVPR2018 Paper: Learning to Compare: Relation Network for Few-Shot Learning

learningtocompare_fsl

PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Few-Shot Learning part)

legal_judgment_prediction_bilstm_att

Legal Juegment Prediction (LJP) with BiLSTM and Attention

legalpapers

Must-read Papers on Legal Intelligence

lemon

开源OA

lengyue-dl

专为验证码而生的深度学习框架

lets_ocr

lic2019-competition

2019语言与智能技术竞赛-基于知识图谱的主动聊天

license-plate-detect-recognition-via-deep-neural-networks-accuracy-up-to-99.9

works in real-time with detection and recognition accuracy up to 99.8% for Chinese license plates: 100 ms/plate

lifelong-learning-paper-list

Lifelong/Continual Learning Paper List

light-lpr

Light-LPR是一个瞄准可以在嵌入式设备、手机端和普通的x86平台上运行的车牌识别开源项目，旨在支持各种场景的车牌识别,车牌字符识别准确率超99.95%，综合识别准确率超过99%，支持目前国内所有的车牌识别，觉得好用的一定要加星哦。

light-task-scheduler

Distributed Scheduled Job Framework

light-weight-refinenet

Light-Weight RefineNet for Real-Time Semantic Segmentation

lightner

Conduct inference with models pre-trained by LD-Net / AutoNER / VanillaNER / ...

lightnet

LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)

lightnetplusplus

LightNet++: Boosted Light-weighted Networks for Real-time Semantic Segmentation

lightnlp

基于Pytorch和torchtext的自然语言处理深度学习框架，包含序列标注、文本分类、句子关系、文本生成、结构分析、知识图谱六大功能模块，已实现了命名实体识别、中文分词、词性标注、语义角色标注、情感分析、关系抽取、语言模型、文本相似度、文本蕴含、依存句法分析、表示学习等功能。框架功能丰富，开箱可用，极易上手！基本都是学习他人实现然后自己修改融合到框架中，没有细致调参，且有不少Bug～