Tea bud detection is a key technology for enabling automated and intelligent tea harvesting. However, accurate detection remains challenging because tea buds are generally small, densely distributed, partially occluded, and visually similar to the surrounding background. In addition, resource-constrained devices impose...
Graph convolutional networks (GCNs) have become a mainstream approach for skeleton-based action recognition by modeling spatial dependencies among human joints. However, existing methods mostly rely on learnable adjacency matrices or average relations over the entire action sequence to construct graph structures. Such...
Qun You, Shao-Qi Zhang, Xia Zou et al.· Journal of Imaging· 0 citations
LCTCANet, a lightweight CNN-Transformer hybrid architecture for remote sensing SR, integrates a core feature extraction module composed of a global contextual local block and an edge-structure fusion block that enables joint learning of global context and local detail.