DA-FSOD: A Novel Data Augmentation Scheme for Few-Shot Object Detection
Deep learning techniques continue to be used in various applications in recent years. However, when it is difficult to obtain adequate training samples, the performance of the depth model will degrade. Although few-shot learning and data enhancement techniques can relieve this dilemma, the diversity...
Үндсэн зохиолчид: | Jian Yao, Tianyun Shi, Xiaoping Che, Jie Yao, Liuyi Wu |
---|---|
Формат: | Өгүүллэг |
Хэл сонгох: | English |
Хэвлэсэн: |
IEEE
2023-01-01
|
Цуврал: | IEEE Access |
Нөхцлүүд: | |
Онлайн хандалт: | https://ieeexplore.ieee.org/document/10227279/ |
Ижил төстэй зүйлс
-
FSOD4RSI: Few-Shot Object Detection for Remote Sensing Images via Features Aggregation and Scale Attention
-н: Honghao Gao, зэрэг
Хэвлэсэн: (2024-01-01) -
Few-shot object detection based on positive-sample improvement
-н: Yan Ouyang, зэрэг
Хэвлэсэн: (2023-10-01) -
Multi-Similarity Enhancement Network for Few-Shot Segmentation
-н: Hao Chen, зэрэг
Хэвлэсэн: (2023-01-01) -
Few-Shot Object Detection in Remote Sensing Image Interpretation: Opportunities and Challenges
-н: Sixu Liu, зэрэг
Хэвлэсэн: (2022-09-01) -
Improving Augmentation Efficiency for Few-Shot Learning
-н: Wonhee Cho, зэрэг
Хэвлэсэн: (2022-01-01)