Abstract
In semantic segmentation, predicting RoI (Region of Interest) classes or objects within small regions faces challenges. To address this issue, we propose Crop&Match, a method to combine RoI cropping and feature matching, to enhance model performance of small RoI classes. The cropping ensures the network to focus on small RoI regions by cropping image regions to contain RoI. And feature matching aligns input images with their RoI cropped versions at a representation level, improving predictive consistency across different perspectives on the same image, thereby boosting RoI class recognition.
| Original language | English |
|---|---|
| Title of host publication | 2023 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9798350344318 |
| DOIs | |
| Publication status | Published - 2023 |
| Event | 2023 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2023 - Busan, Korea, Republic of Duration: 2023 Oct 23 → 2023 Oct 25 |
Publication series
| Name | 2023 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2023 |
|---|
Conference
| Conference | 2023 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2023 |
|---|---|
| Country/Territory | Korea, Republic of |
| City | Busan |
| Period | 23/10/23 → 23/10/25 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Keywords
- contrastive learning
- disease
- plant
- semantic segmentation
- small object detection
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Media Technology
- Instrumentation
- Artificial Intelligence
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