Loss Architecture Search for Few-Shot Object Recognition
Few-shot object recognition, which exploits a set of well-labeled data to build a classifier for new classes that have only several samples per class, has received extensive attention from the machine learning community. In this paper, we investigate the problem of designing an optimal loss function...
Saved in:
Main Authors: | Jun Yue, Zelang Miao, Yueguang He, Nianchun Du |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2020-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2020/1041962 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Few-shot Learning: Methods and Applications
by: Li Jiaxiang, et al.
Published: (2025-01-01) -
Few-Shot Contrail Segmentation in Remote Sensing Imagery With Loss Function in Hough Space
by: Junzi Sun, et al.
Published: (2025-01-01) -
Few-shot Remote Sensing Imagery Recognition with Compositionality Inductive Bias in Hierarchical Representation Space
by: Shichao Zhou, et al.
Published: (2025-01-01) -
Learning under label noise through few-shot human-in-the-loop refinement
by: Aaqib Saeed, et al.
Published: (2025-02-01) -
Segment anything model for few-shot medical image segmentation with domain tuning
by: Weili Shi, et al.
Published: (2024-11-01)