Recent advances on loss functions in deep learning for computer vision
The loss function, also known as cost function, is used for training a neural network or other
machine learning models. Over the past decade, researchers have designed many loss …
machine learning models. Over the past decade, researchers have designed many loss …
Wise-IoU: bounding box regression loss with dynamic focusing mechanism
The loss function for bounding box regression (BBR) is essential to object detection. Its good
definition will bring significant performance improvement to the model. Most existing works …
definition will bring significant performance improvement to the model. Most existing works …
Mpdiou: a loss for efficient and accurate bounding box regression
S Ma, Y Xu - arxiv preprint arxiv:2307.07662, 2023 - arxiv.org
Bounding box regression (BBR) has been widely used in object detection and instance
segmentation, which is an important step in object localization. However, most of the existing …
segmentation, which is an important step in object localization. However, most of the existing …
UAV-YOLOv8: A small-object-detection model based on improved YOLOv8 for UAV aerial photography scenarios
Unmanned aerial vehicle (UAV) object detection plays a crucial role in civil, commercial, and
military domains. However, the high proportion of small objects in UAV images and the …
military domains. However, the high proportion of small objects in UAV images and the …
-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression
Bounding box (bbox) regression is a fundamental task in computer vision. So far, the most
commonly used loss functions for bbox regression are the Intersection over Union (IoU) loss …
commonly used loss functions for bbox regression are the Intersection over Union (IoU) loss …
Plant disease recognition model based on improved YOLOv5
Z Chen, R Wu, Y Lin, C Li, S Chen, Z Yuan, S Chen… - Agronomy, 2022 - mdpi.com
To accurately recognize plant diseases under complex natural conditions, an improved plant
disease-recognition model based on the original YOLOv5 network model was established …
disease-recognition model based on the original YOLOv5 network model was established …
A comprehensive review of deep learning-based PCB defect detection
X Chen, Y Wu, X He, W Ming - IEEE Access, 2023 - ieeexplore.ieee.org
A printed circuit board (PCB) functions as a substrate essential for interconnecting and
securing electronic components. Its widespread integration is evident in modern electronic …
securing electronic components. Its widespread integration is evident in modern electronic …
Boosting R-CNN: Reweighting R-CNN samples by RPN's error for underwater object detection
Complicated underwater environments bring new challenges to object detection, such as
unbalanced light conditions, low contrast, occlusion, and mimicry of aquatic organisms …
unbalanced light conditions, low contrast, occlusion, and mimicry of aquatic organisms …
Rachis detection and three-dimensional localization of cut off point for vision-based banana robot
F Wu, J Duan, P Ai, Z Chen, Z Yang, X Zou - Computers and Electronics in …, 2022 - Elsevier
For the operation and visual positioning of a banana robot, it is important to accurately
position the rachis and cut off point. However, the main factors that affect the three …
position the rachis and cut off point. However, the main factors that affect the three …
Robust few-shot aerial image object detection via unbiased proposals filtration
Few-shot aerial image object detection aims to rapidly detect object instances of novel
category in aerial images by using few labeled samples. However, due to the complex …
category in aerial images by using few labeled samples. However, due to the complex …