Yolov11: An overview of the key architectural enhancements

R Khanam, M Hussain - arxiv preprint arxiv:2410.17725, 2024‏ - arxiv.org
This study presents an architectural analysis of YOLOv11, the latest iteration in the YOLO
(You Only Look Once) series of object detection models. We examine the models …

[PDF][PDF] YOLOv1 to YOLOv10: The fastest and most accurate real-time object detection systems

CY Wang, HYM Liao - APSIPA Transactions on Signal and …, 2024‏ - nowpublishers.com
This is a comprehensive review of the YOLO series of systems. Different from previous
literature surveys, this review article reexamines the characteristics of the YOLO series from …

[HTML][HTML] Comparing YOLOv8 and Mask R-CNN for instance segmentation in complex orchard environments

R Sapkota, D Ahmed, M Karkee - Artificial Intelligence in Agriculture, 2024‏ - Elsevier
Instance segmentation, an important image processing operation for automation in
agriculture, is used to precisely delineate individual objects of interest within images, which …

Interpretability research of deep learning: A literature survey

B Xua, G Yang - Information Fusion, 2024‏ - Elsevier
Deep learning (DL) has been widely used in various fields. However, its black-box nature
limits people's understanding and trust in its decision-making process. Therefore, it becomes …

In-depth review of yolov1 to yolov10 variants for enhanced photovoltaic defect detection

M Hussain, R Khanam - Solar, 2024‏ - mdpi.com
This review presents an investigation into the incremental advancements in the YOLO (You
Only Look Once) architecture and its derivatives, with a specific focus on their pivotal …

Yolov5, yolov8 and yolov10: The go-to detectors for real-time vision

M Hussain - arxiv preprint arxiv:2407.02988, 2024‏ - arxiv.org
This paper presents a comprehensive review of the evolution of the YOLO (You Only Look
Once) object detection algorithm, focusing on YOLOv5, YOLOv8, and YOLOv10. We analyze …

[HTML][HTML] Enhanced self-checkout system for retail based on improved yolov10

L Tan, S Liu, J Gao, X Liu, L Chu, H Jiang - Journal of Imaging, 2024‏ - mdpi.com
With the rapid advancement of deep learning technologies, computer vision has shown
immense potential in retail automation. This paper presents a novel self-checkout system for …

Bgf-yolo: Enhanced yolov8 with multiscale attentional feature fusion for brain tumor detection

M Kang, CM Ting, FF Ting, RCW Phan - International Conference on …, 2024‏ - Springer
Abstract You Only Look Once (YOLO)-based object detectors have shown remarkable
accuracy for automated brain tumor detection. In this paper, we develop a novel BGF-YOLO …

Rt-detrv2: Improved baseline with bag-of-freebies for real-time detection transformer

W Lv, Y Zhao, Q Chang, K Huang, G Wang… - arxiv preprint arxiv …, 2024‏ - arxiv.org
In this report, we present RT-DETRv2, an improved Real-Time DEtection TRansformer (RT-
DETR). RT-DETRv2 builds upon the previous state-of-the-art real-time detector, RT-DETR …

[HTML][HTML] Sod-yolo: Small-object-detection algorithm based on improved yolov8 for uav images

Y Li, Q Li, J Pan, Y Zhou, H Zhu, H Wei, C Liu - Remote Sensing, 2024‏ - mdpi.com
The rapid development of unmanned aerial vehicle (UAV) technology has contributed to the
increasing sophistication of UAV-based object-detection systems, which are now extensively …