Results 31 to 40 of about 6,685 (188)

Lightweight Object Detection Algorithm for Electric Meter Calibration Line

Shuju Caiji Yu Chuli
In the industrial production line scenario， target detection technology with visual information has become a new hotspot for intelligent production， providing decision‑making information for fault detection and elimination.
DONG Xianguang, SUN Yanling, DAI Yanjie, XING Yu, ZHAI Xiaohui, SUN Kai, LYU Yuchao, WU Qiang, LIU Ju   +8 more
doaj   +1 more source

A Hybrid Fuzzy–Support Vector Machine Framework for Real‐Time Dust Detection and Thermal Mapping in Photovoltaic Panels

Energy Science &Engineering, EarlyView.
A hybrid Fuzzy–SVM framework for real‐time dust detection and thermal mapping in PV panels. ABSTRACT Dust accumulation significantly degrades the energy output of photovoltaic (PV) panels, particularly in arid and semi‐arid regions. While existing studies have separately explored image‐based dust detection, environmental modeling, and machine learning (
Debasish Sarker, S. M. Rezaul Karim, MD. Shouquat Hossain, Md. Moshaddek Hossain, Md. Monirul Kabir   +4 more
wiley   +1 more source

Detection of Keratoconus through YOLOv8 Region of Interest Preprocessing and Pre-trained Convolutional Neural Networks Using 2D Images

Cyprus Journal of Medical Sciences
BACKGROUND/AIMS: This study presents a methodology for detecting keratoconus using pre-trained convolutional neural network (CNN) models. Five models were evaluated, namely, Xception, InceptionV3, ResNet152, InceptionResNetV2, and EfficientNetV2S ...
Muhammed Sideeq Anwar, Emre Özbilge
doaj   +1 more source

YOLOv8-GRW:A YOLOv8-based Algorithm for Road Defect Detection

Information Technology and Control
Given the critical importance of road defect detection for ensuring vehicular safety and the inefficiencies and high costs associated with traditional detection methods, this paper introduces an enhanced road defect detection algorithm based on an improved YOLOv8-GRW model.
Ao Xu, Dong Wang, Yongjian Zhu, Du Yang, Yintian Xu   +4 more
openaire   +1 more source

EDGS-YOLOv8: An Improved YOLOv8 Lightweight UAV Detection Model

Drones
In the rapidly developing drone industry, drone use has led to a series of safety hazards in both civil and military settings, making drone detection an increasingly important research field. It is difficult to overcome this challenge with traditional object detection solutions.
Min Huang, Wenkai Mi, Yuming Wang
openaire   +2 more sources

Matching habitat choice could be brightness‐based instead of hue‐based in green‐brown polymorphic grasshoppers

Oikos, EarlyView.
Some prey species have evolved background matching, that is they resemble their surrounding environment in terms of colour and/or brightness. When prey populations inhabit patchy environments, they may even have evolved specialised phenotypes: each phenotype matching a specific subset of patches.
Lilian Cabon, Holger Schielzeth
wiley   +1 more source

WASTEWISE: AI-POWERED WASTE EDUCATION FOR ELEMENTARY STUDENTS USING YOLOV8 AND ESP32-CAM

Pilar Nusa Mandiri
The growing volume of global waste poses a significant challenge for effective waste management, particularly in developing countries where awareness and practices around waste sorting remain limited. This study aims to enhance elementary school students'
Kenny Aldi, Yan Rianto
doaj   +1 more source

The potential of seedbank digital information in plant conservation

PLANTS, PEOPLE, PLANET, EarlyView.
Seedbanks are vital for biodiversity conservation, but their potential remains underutilised due to a limited understanding of the intraspecific genetic diversity they hold. By leveraging digitised data associated with seedbank collections, such as sampling locations, number of maternal plants and seed traits, we can attempt the estimation of genetic ...
Roberta Gargiulo, Sean Hoban, Anne M. Visscher, Pablo Gómez Barreiro, Roberta L. C. Dayrell, Kiran L. Dhanjal‐Adams, Alice R. Hudson, Charlotte E. Seal, Simon Kallow, Jan Sala, Lee Oliver, Naomi Carvey, Ted Chapman, Efisio Mattana, Clare Callow, Christopher Cockel, Michael F. Fay, Juan Viruel, Inna Birchenko, Stephanie Miles, Timothy Pearce, Paul Kersey, Elinor Breman, Kate A. Hardwick   +23 more
wiley   +1 more source

Application of YOLOv8 Architecture Optimized based on BiFPN in Leather Defect Recognition

Pige Kexue Yu Gongcheng
Traditional image processing methods are difficult to effectively deal with complex backgrounds and defects with different scales. This paper proposed a YOLOv8 architecture optimization strategy that integrates Bidirectional Feature Pyramid Network ...
Hao TANG, Faming CHEN, Zhipeng FENG, Lingzhi HE   +3 more
doaj   +1 more source

CFE-YOLOv8s: Improved YOLOv8s for Steel Surface Defect Detection

Electronics
Due to the low detection accuracy in steel surface defect detection and the constraints of limited hardware resources, we propose an improved model for steel surface defect detection, named CBiF-FC-EFC-YOLOv8s (CFE-YOLOv8s), including CBS-BiFormer (CBiF) modules, Faster-C2f (FC) modules, and EMA-Faster-C2f (EFC) modules.
Shuxin Yang, Yang Xie, Jianqing Wu, Weidong Huang, Hongsheng Yan, Jingyong Wang, Bi Wang, Xiangchun Yu, Qiang Wu, Fei Xie   +9 more
openaire   +1 more source