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xiaogaogaoxiao's Projects

latticelstm icon latticelstm

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

lcgnet icon lcgnet

An implementation of ‘’Learned Conjugate Gradient Descent Network for Massive MIMO Detection‘’

ldamp_based-channel-estimation icon ldamp_based-channel-estimation

This code is for the following paper: H. He, C. Wen, S. Jin, and G. Y. Li, “Deep learning-based channel estimation for beamspace mmwave massive MIMO systems,” IEEE Wireless Commun. Lett., vol. 7, no. 5, pp. 852–855, Oct. 2018.

ldbp icon ldbp

Physics-Based Deep Learning for Fiber-Optic Communication Systems

ldsm icon ldsm

Layered Data Security Model for Edge Computing

learn2branch-ecole icon learn2branch-ecole

Reimplementation of "Exact Combinatorial Optimization with Graph Convolutional Neural Networks" (NeurIPS 2019)

learn_prox_ops icon learn_prox_ops

Implementation of "Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems"

learning-tool-for-deaf-mute icon learning-tool-for-deaf-mute

This a learning assistance tool for deaf-mute children who tries to learn Bengali sign language. This tool helps them to learn Bengali letters, practice their learning and test them self about what they have learnt. This Project has been awarded by IEEE Bangladesh Section in SS12 Innovation challenge and Maker fair 2018.

leo-ho-project icon leo-ho-project

Handover Self-Optimization in Drones Based on Low Earth Orbit Satellite Systems Project Codes

lfcis icon lfcis

Algorithm LFCIS published in IEEE Access 2018, Graph clustering, community summarization

libl1spirit.so icon libl1spirit.so

This code was released via Mark Murphy based on “Fast L1-SPIRiT Compressed Sensing Parallel Imaging MRI: Scalable Parallel Implementation and Clinically Feasible Runtime”, IEEE Transactions on Medical Imaging, volume 31, issue 6, pages 1250-1262.

license-plate-recognization-pytorch icon license-plate-recognization-pytorch

该工作的内容主要是面向**车牌识别系统。车牌的检测系统通过YOLOv3网络来实现,检测后的车牌会通过空间变换网络进行倾斜校正。校正后的图片经由LPRNet进行识别。目前在1000张图片上测试的最终准确率可达93.3%。实现者电子科技大学刘俊凯、陈昂、夏子寒

linkschedulinggnns_supervisionstudy icon linkschedulinggnns_supervisionstudy

A comparative study of different supervision levels (supervised/unsupervised/self-supervised) when training graph neural network models for link scheduling in wireless networks.

lis-deeplearning icon lis-deeplearning

Simulation code for "Enabling Large Intelligent Surfaces with Compressive Sensing and Deep Learning" by Abdelrahman Taha, Muhammad Alrabeiah, Ahmed Alkhateeb, arXiv e-prints, p. arXiv:1904.10136, Apr 2019.

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