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Found 8 papers, 2 papers with code
Dual-feature Fusion Attention Network for Small Object Segmentation
In this paper, we propose a dual feature fusion attention network (DFF-Net) to improve the segmentation accuracy of small objects.
Identification of Molecular Subtypes and a Prognostic Signature Based on Inflammation-Related Genes in Colon Adenocarcinoma
We finally used qRT–PCR to detect the expression levels of four genes in colon cancer cell lines and obtained results consistent with the prediction.
High-fidelity acoustic signal enhancement for phase-OTDR using supervised learning
The results show that, the proposed method can well suppress the noise and signal distortion caused by the laser frequency drift, laser phase noise, and interference fading, while recover the acoustic signals with high fidelity.
Recurrent Interaction Network for Jointly Extracting Entities andClassifying Relations
In this study, we argue that an explicit interaction between the NER model and the RE model will better guide the training of both models.
Spatiotemporal Multi-Graph Convolution Networkfor Ride-hailing Demand Forecasting
This task is challenging due to the complicated spatiotemporal dependencies among regions.
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting
The output of the three components are weighted fused to generate the final prediction results.
Ranked #14 on
Traffic Prediction
on PeMS07
Multi-branch fusion network for hyperspectral image classification
Furthermore, the L2 regularization is introduced into this work to improve the generalization performance of the proposed model under small sample set.
Unidirectional brain to muscle connectivity reveals motor cortex control of leg muscles during stereotyped walking
One sentence summary: Motor cortex proactively drives contralateral swing leg muscles during treadmill walking, counter to the traditional view of stereotyped human locomotion
