5 accepted papers
Graph anomaly detection is emerging as a critical technology for addressing increasingly complex and dynamic risk environments. Although unsupervised graph anomaly detection has advanced under the graph representation learning, directly applying these paradigms remains fundamentally misaligned with
Multi-view learning aims to enhance performance by integrating information from multiple sources. While different views offer complementary perspectives, extracting consistent and discriminative representations remains a significant challenge due to discrepancies in representation and presence of no
Robots operating in agricultural environments require a robust, fast perception system to accurately identify picking points. This paper proposed a lightweight method for detecting sweet pepper peduncles, which uses an active illumination camera system and DUTU<sup xmlns:mml="http://www.w3.org/1998/
Over-smoothing is a persistent challenge in Graph Neural Networks (GNNs), where node embeddings become indistinguishable as network depth increases, fundamentally limiting their effectiveness on tasks requiring fine-grained distinctions. This issue arises from the reliance on diffusion-based propaga
The aging population and diminishing working population in agriculture motivate the development of autonomous harvesting robots. Although autonomous harvesting is expanding rapidly, the commercial application of sweet pepper harvesting robots still faces challenges. This paper presents the developme…