DouN-GNN:Double nodes graph neural network for few-shot learning.

EDFIDepth: enriched multi-path vision transformer feature interaction networks for monocular depth estimation.

Boundary enhancement and refinement network for camouflaged object detection.

PCDR-DFF: multi-modal 3D object detection based on point cloud diversity representation and dual feature fusion.

A multi-scale hierarchical node graph neural network for few-shot learning.

PCTDepth: Exploiting Parallel CNNs and Transformer via Dual Attention for Monocular Depth Estimation.

MonoSAID: Monocular 3D Object Detection based on Scene-Level Adaptive Instance Depth Estimation.

MFCINet: multi-level feature and context information fusion network for RGB-D salient object detection.

Detection of Tea Leaf Blight in Low-Resolution UAV Remote Sensing Images.

RCFNet: Related cross-level feature network with cascaded self-distillation for monocular depth estimation.

CEMINet: Context exploration and multi-level interaction network for salient object detection.

ECW-EGNet: Exploring Cross-ModalWeighting and edge-guided decoder network for RGB-D salient object detection.

CTA-Net: A gaze estimation network based on dual feature aggregation and attention cross fusion.

A Lightweight Multimodal Footprint Recognition Network Based on Progressive Multi-Granularity Feature Fusion.

Multi-scale confusion and filling mechanism for pressure footprint recognition.

MSEC: Multi-Scale Erasure and Confusion for fine-grained image classification.

Detection and severity analysis of tea leaf blight based on deep learning.

Identification of tea leaf diseases by using an improved deep convolutional neural network.

A low shot learning method for tea leaf's disease identification.

Part-Based Attribute-Aware Network for Person Re-Identification.