Detection and tracking of safety helmet wearing based on deep learning
Open Computer ScienceFailure to wear a helmet correctly is a significant cause of injury or death in the construction industry and industrial production. Traditional supervision methods predominantly rely on manual oversight, incurring substantial costs and demonstrating ...
Liang Hua +4 more
doaj +1 more source
YOLOv5 vs. YOLOv8 in Marine Fisheries: Balancing Class Detection and Instance Count
This paper presents a comparative study of object detection using YOLOv5 and YOLOv8 for three distinct classes: artemia, cyst, and excrement. In this comparative study, we analyze the performance of these models in terms of accuracy, precision, recall ...
Boymelgreen, Alicia +4 more
core
Non-Destructive Testing and Machine Learning in Inspection of Post-Tensioned Concrete Bridges [PDF]
Bridges are critical infrastructures essential for transportation and economic activities yet face accelerated deterioration from environmental factors and increased usage.
Wie, Mathias Føyner
core
Real Time Student Emotion Detection using Yolov5 [PDF]
The introduction of technology in the field of Education, especially in learner emotion detection plays an important role in the modern educational context.
Bimantoro, Fitri +2 more
core +1 more source
Forest fire detection and recognition method based on improved YOLOv5-ACE algorithm. [PDF]
PLoS OneZhao Y, Tang C.
europepmc +1 more source
DRIP INFUSION MONITORING AND DATA LOGGING SYSTEM BASED ON YOLOv5 [PDF]
Intravenous infusion (IV) functions to deliver medication or fluids directly into the patient’s body and requires an accurate drops-per-minute (TPM) calculation to ensure the correct dosage is administered.
Kinasih, Indira Puteri +3 more
core +1 more source
Retraction Note: Accurate and real-time brain tumour detection and classification using optimized YOLOv5 architecture. [PDF]
Sci RepSaranya M, Praveena R.
europepmc +1 more source
Computer vision models for precision poultry farming: A narrative review of behavioral and welfare monitoring studies. [PDF]
Poult SciPaneru B +6 more
europepmc +1 more source
Urological diagnostics based on kidney stone detection in CT imaging using YOLOv8 deep learning framework. [PDF]
Front Med (Lausanne)Ye Y, Chipusu K, He L, Shen S, Huang J.
europepmc +1 more source
Comparing YOLOv8 to YOLOv5 for Pose Estimation Supporting Automated Aerial Refueling [PDF]
This work used the newly released YOLO version 8 Object Detection as a feature detector for a monocular pose estimation pipeline and showed up to an 83.6% reduction in translation error when compared to YOLOv5.
Friesenhahn, Dawson
core +1 more source