BGF-YOLO: Enhanced YOLOv8 with Multiscale Attentional Feature Fusion for Brain Tumor Detection [PDF]
Ming Kang +3 more
openalex +1 more source
Pediatric Wrist Fracture Detection Using Feature Context Excitation Modules in X‐Ray Images
This study aims to propose novel neural network models serving as computer‐assisted diagnosis (CAD) tools to assist surgeons in diagnosing pediatric wrist fractures. This study integrates multiple independent blocks into the YOLOv8 model and presents three methods to enhance the model architecture, aiming to improve overall performance.
Rui‐Yang Ju +3 more
wiley +1 more source
SD-YOLOv8: An Accurate Seriola dumerili Detection Model Based on Improved YOLOv8
Accurate identification of Seriola dumerili (SD) offers crucial technical support for aquaculture practices and behavioral research of this species. However, the task of discerning S. dumerili from complex underwater settings, fluctuating light conditions, and schools of fish presents a challenge.
Mingxin Liu +5 more
openaire +3 more sources
Lightweight Apple Leaf Disease Detection Algorithm Based on Improved YOLOv8
[Objective]As one of China's most important agricultural products, apples hold a significant position in cultivation area and yield. However, during the growth process, apples are prone to various diseases that not only affect the quality of the fruit ...
LUO Youlu +3 more
doaj +1 more source
A Robust Multi‐Oriented License Plate Detector and A Derived End‐to‐End License Plate Recognizer
This is a research paper on license plate detection and recognition. A new center‐aware license plate detection and end‐to‐end license plate recognition framework is proposed for robust and efficient license plate detection and recognition under unconstrained scenarios.
Xudong Fan, Wei Zhao
wiley +1 more source
YOLOv8-MDS: A YOLOv8-Based Multi-Distance Scale Drone Detection Network
Abstract Drones have become widely used across various fields, showcasing their capabilities while also raising significant security and privacy concerns. Current detection methods, such as radar, radio frequency, and acoustic detection systems, face issues like high costs and poor interference resistance.
Mingxi Chen +3 more
openaire +1 more source
Enhanced Yolov8 with OpenCV for Blind-Friendly Object Detection and Distance Estimation
The development of computer technology and computer vision has had a significant positive impact on the daily lives of blind people, especially in efforts to improve their navigation abilities.
Erwin Syahrudin +2 more
doaj +1 more source
Multi‐Channel Fusion Residual Network for Robust Bone Fracture Classification From Radiographs
This research introduces a multi‐channel fusion residual network (MFResNet18) to enhance bone fracture classification from radiographs. By integrating a multi‐modal channel filter with multi‐path early feature extraction, the model enriches fracture‐specific details before deep inference. Experimental results demonstrate a classification accuracy of 99.
Sivapriya T +3 more
wiley +1 more source
MUTI-YOLOV8: YOLOV8-based target detection algorithm for stacked objects
In order to solve the problems of low accuracy, missed detection and false detection of stacked objects in the existing object detection, an improved algorithm model based on YOLOV8 was proposed. The model introduces Deformable Convolutiona Networks. The Shueffle Attention mechanism is added to reduce the complexity of the model and improve the ability
Yuchen Xu +4 more
openaire +1 more source

