Results 1 to 10 of about 8,004 (205)
SerpensGate-YOLOv8: an enhanced YOLOv8 model for accurate plant disease detection
Frontiers in Plant SciencePlant disease detection remains a significant challenge, necessitating innovative approaches to enhance detection efficiency and accuracy. This study proposes an improved YOLOv8 model, SerpensGate-YOLOv8, specifically designed for plant disease detection tasks.
Xiaoyu Zhou, Zhou Xiaoyu
exaly +4 more sources
EDGS-YOLOv8: An Improved YOLOv8 Lightweight UAV Detection Model
DronesIn 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
exaly +3 more sources
CES-YOLOv8: Strawberry Maturity Detection Based on the Improved YOLOv8
AgronomyAutomatic harvesting robots are crucial for enhancing agricultural productivity, and precise fruit maturity detection is a fundamental and core technology for efficient and accurate harvesting. Strawberries are distributed irregularly, and their images contain a wealth of characteristic information.
Fenglin Zhong +2 more
exaly +3 more sources
Human Activities Detection using DeepLearning Technique- YOLOv8 [PDF]
ITM Web of Conferences, 2023 Using a mask during the pandemic has occasionally been crucial and difficult. The use of universal masks can greatly lower and possibly even stop the spread of viruses within communities.
Motwani Nilesh Parmanand, S Soumya
doaj +1 more source
In Situ Identification Method of Maize Stalk Width Based on Binocular Vision and Improved YOLOv8
智慧农业, 2023 ObjectiveThe width of maize stalks is an important indicator affecting the lodging resistance of maize. The measurement of maize stalk width has many problems, such as cumbersome manual collection process and large errors in the accuracy of automatic ...
ZUO Haoxuan +5 more
doaj +1 more source
BL-YOLOv8: An Improved Road Defect Detection Model Based on YOLOv8
Sensors, 2023 Road defect detection is a crucial task for promptly repairing road damage and ensuring road safety. Traditional manual detection methods are inefficient and costly. To overcome this issue, we propose an enhanced road defect detection algorithm called BL-YOLOv8, which is based on YOLOv8s.
Xueqiu Wang +3 more
openaire +3 more sources
Design of an Intelligent Energy Management Prototype for an Electric Lighting Network on a Raspberry Pi Board [PDF]
ITM Web of ConferencesEfficient management of street lighting is crucial for cities seeking to reduce their energy consumption and greenhouse gas emissions. This paper proposes an innovative approach that dynamically adjusts the brightness of streetlights according to two key
Jouahri Mohammed Amine +5 more
doaj +1 more source
Study on Spark Image Detection for Abrasive Belt Grinding via Transfer Learning with YOLOv8
SensorsAiming to solve the problems of low precision and poor efficiency caused by relying on manual experience during the manual polishing of blades, a multi-view spark image detection method based on YOLOv8 transfer learning is proposed.
Jian Huang, Guangpeng Zhang
doaj +1 more source
Jurnal Kelautan TropisCultivation of Litopenaeus vannamei shrimp is an important fishery commodity in Indonesia. Providing the right amount of feed is crucial for optimal shrimp growth. The amount of feed given greatly depends on the measurement of shrimp length.
Erwin Adriono +2 more
doaj +1 more source
YOLOv8-GRW:A YOLOv8-based Algorithm for Road Defect Detection
Information Technology and ControlGiven 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 +4 more
openaire +1 more source