Adaptive Focal Loss for Keypoint-Based Deep Learning Detectors Addressing Class Imbalance

Adaptive Focal Loss for Keypoint-Based Deep Learning Detectors Addressing Class Imbalance

Keypoint-based deep learning detectors have proven highly effective in object detection tasks by predicting specific keypoints to determine object classification and location. Examples include CornerNet, CenterNet, ExtremeNet, RetinaNet, FCOS, and ObjectBox. Despite their strengths, these methods ar...

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Bibliographic Details
Main Authors: Zhihao Su, Afzan Adam, Mohammad Faidzul Nasrudin
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Deep learning algorithm
object detection
keypoint-based deep learning detector
class imbalance
sampling method
Online Access:https://ieeexplore.ieee.org/document/10872927/
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