Search Results for author:
Found 3 papers, 0 papers with code
Fastidious Attention Network for Navel Orange Segmentation
Deep learning achieves excellent performance in many domains, so we not only apply it to the navel orange semantic segmentation task to solve the two problems of distinguishing defect categories and identifying the stem end and blossom end, but also propose a fastidious attention mechanism to further improve model performance.
FSD: Feature Skyscraper Detector for Stem End and Blossom End of Navel Orange
To accurately and efficiently distinguish the stem end and the blossom end of navel orange from its black spots, we propose a feature skyscraper detector (FSD) with low computational cost, compact architecture and high detection accuracy.
Multi-vision Attention Networks for On-line Red Jujube Grading
To solve the red jujube classification problem, this paper designs a convolutional neural network model with low computational cost and high classification accuracy.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
