most citedLIPS: A Light Intensity Based Positioning System For Indoor Environments

9 citations · 25 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG20197 cited

Interpreting and Understanding Graph Convolutional Neural Network using Gradient-based Attribution Method

Shangsheng Xie, Mingming Lu

To solve the problem that convolutional neural networks (CNNs) are difficult to process non-grid type relational data like graphs, Kipf et al. proposed a graph convolutional neural…

cs.CV20194 cited

Graph Hierarchical Convolutional Recurrent Neural Network (GHCRNN) for Vehicle Condition Prediction

Mingming Lu, Kunfang Zhang, Haiying Liu +1

The prediction of urban vehicle flow and speed can greatly facilitate people's travel, and also can provide reasonable advice for the decision-making of relevant government departm…

cs.AI20195 cited

Program Classification Using Gated Graph Attention Neural Network for Online Programming Service

Mingming Lu, Dingwu Tan, Naixue Xiong +2

The online programing services, such as Github,TopCoder, and EduCoder, have promoted a lot of social interactions among the service users. However, the existing social interactions…

cs.LG2019

Based on Graph-VAE Model to Predict Student's Score

Yang Zhang, Mingming Lu

The OECD pointed out that the best way to keep students up to school is to intervene as early as possible [1]. Using education big data and deep learning to predict student's score…

cs.NI20149 cited

LIPS: A Light Intensity Based Positioning System For Indoor Environments

Bo Xie, Guang Tan, Yunhuai Liu +3

This paper presents LIPS, a Light Intensity based Positioning System for indoor environments. The system uses off-the-shelf LED lamps as signal sources, and uses light sensors as s…