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...
Κύριοι συγγραφείς: | Jian Yao, Tianyun Shi, Xiaoping Che, Jie Yao, Liuyi Wu |
---|---|
Μορφή: | Άρθρο |
Γλώσσα: | English |
Έκδοση: |
IEEE
2023-01-01
|
Σειρά: | IEEE Access |
Θέματα: | |
Διαθέσιμο Online: | https://ieeexplore.ieee.org/document/10227279/ |
Παρόμοια τεκμήρια
Παρόμοια τεκμήρια
-
FSOD4RSI: Few-Shot Object Detection for Remote Sensing Images via Features Aggregation and Scale Attention
ανά: Honghao Gao, κ.ά.
Έκδοση: (2024-01-01) -
Few-shot object detection based on positive-sample improvement
ανά: Yan Ouyang, κ.ά.
Έκδοση: (2023-10-01) -
Multi-Similarity Enhancement Network for Few-Shot Segmentation
ανά: Hao Chen, κ.ά.
Έκδοση: (2023-01-01) -
Few-Shot Object Detection in Remote Sensing Image Interpretation: Opportunities and Challenges
ανά: Sixu Liu, κ.ά.
Έκδοση: (2022-09-01) -
Improving Augmentation Efficiency for Few-Shot Learning
ανά: Wonhee Cho, κ.ά.
Έκδοση: (2022-01-01)