IEEE

Convolution Self-Guided Transformer for Diagnosis and Recognition of Crop Disease in Different Environments

Abstract: Accurately diagnosing crop diseases is crucial for agricultural productivity and food safety. This study addresses the challenge by developing an AI crop disease diagnosis platform, ...
IEEE

Graph Linear Convolution Pooling for Learning in Incomplete High-Dimensional Data

Abstract: High-dimensional and incomplete (HDI) data are frequently encountered in diverse real-world applications involving complex interactions among numerous nodes. Approaches based on latent ...
Frontiers

Application of real-time detection transformer based on convolutional block attention module and grouped convolution in maize seedling

Introduction: The intelligent detection and counting of maize seedlings constitute crucial components in future smart maize cultivation and breeding. However, the detection of maize seedlings in field ...
Frontiers

MAUNet: a mixed attention U-net with spatial multi-dimensional convolution and contextual feature calibration for 3D brain tumor segmentation in multimodal MRI

1 The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China 2 College of Information Engineering, Henan University of Science and ...