M
Min Deng
Researcher at Central South University
Publications - 19
Citations - 1800
Min Deng is an academic researcher from Central South University. The author has contributed to research in topics: Convolutional neural network & Feature (computer vision). The author has an hindex of 8, co-authored 19 publications receiving 580 citations.
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T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction
TL;DR: In this article, a novel neural network-based traffic forecasting method, the temporal graph convolutional network (T-GCN) model, which is combined with the graph convolutionsal network and the gated recurrent unit (GRU), is proposed.
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Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method.
TL;DR: Experiments demonstrate that the T-GCN model can obtain the spatiotemporal correlation from traffic data and the predictions outperform state-of-art baselines on real-world traffic datasets.
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RSI-CB: A Large Scale Remote Sensing Image Classification Benchmark via Crowdsource Data
TL;DR: The experiments show that RSI-CB is more suitable as a benchmark for remote sensing image classification tasks than other benchmarks in the big data era and has many potential applications.
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Learning to Measure Change: Fully Convolutional Siamese Metric Networks for Scene Change Detection
TL;DR: Thresholded Contrastive Loss (TCL) is proposed with a more tolerant strategy to punish noisy changes to address the issue of large viewpoint differences and a novel fully Convolutional siamese metric Network (CosimNet) to measure changes by customizing implicit metrics.
Journal ArticleDOI
Multi-Scale Spatial and Channel-wise Attention for Improving Object Detection in Remote Sensing Imagery
TL;DR: Experiments show that the mean average precision of object detection is improved after the addition of MSCA to the current object detection model, and the proposed multi-scale spatial and channel-wise attention mechanism to answer this question.