Shuiguang Deng

SCAU-Net: Spatial-Channel Attention U-Net for Gland Segmentation

2020 · Frontiers in Bioengineering and Biotechnology

With the development of medical technology, image semantic segmentation is of great significance for morphological analysis, quantification, and diagnosis of human tissues. However, manual detection and segmentation is a time-consuming task. Especially for biomedical image, …

ExploraCoder: Advancing code generation for multiple unseen APIs via planning and chained exploration

2024 · arXiv (Cornell University)

Large language models face intrinsic limitations in coding with APIs that are unseen in their training corpora. As libraries continuously evolve, it becomes impractical to exhaustively retrain LLMs with new API knowledge. This limitation hampers …

<i>KeAD:</i> <i>K</i>nowledge-<i>e</i>nhanced Graph Attention Network for Accurate <i>A</i>nomaly <i>D</i>etection

2025 · IEEE Transactions on Services Computing

Anomaly detection has emerged as one of the core research topics to support workflow applications across various domains. To differentiate anomalies from underlying normal patterns of workflows, Graph Neural Networks (GNNs) models have been introduced. …

On Deep Learning for Trust-Aware Recommendations in Social Networks

2016 · IEEE Transactions on Neural Networks and Learning Systems

With the emergence of online social networks, the social network-based recommendation approach is popularly used. The major benefit of this approach is the ability of dealing with the problems with cold-start users. In addition to …