Results 71 to 80 of about 19,743 (267)

A Study on the Detection of Hole in Automotive CV Joint Boot Using Image Processing and AI Techniques [PDF]

open access: yes한국정밀공학회지
Detecting and analyzing defects in components or systems is crucial for maintaining high-quality standards in modern manufacturing and quality control.
Yun-Hyeok Lim, Hyeongill Lee
doaj   +1 more source

Hexapod Locomotion Across Structured and Unstructured Terrains: A Data‐Driven Review of Modeling, Control, and Validation

open access: yesJournal of Field Robotics, EarlyView.
ABSTRACT The design of a hexapod is complex and requires integration between kinematic models, control systems, and sensing. Existing literature has reviewed these sub‐systems in isolation. Since 2021, there has been no review of the field despite significant advancements in soft soil, lunar traversal, and artificial intelligence.
Akhil Rampersad, Bashan Naidoo
wiley   +1 more source

Machine learning‐driven advances in carbon‐based quantum dots: Opportunities accompanied by challenges

open access: yesResponsive Materials, EarlyView.
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen   +8 more
wiley   +1 more source

Water Level Detection and Flood Early Warning System Using Image Processing

open access: yesJournal of Electrical Engineering and Computer
Image processing is a crucial method in modern technology, enabling computers to analyze and extract information from images or videos. This study focuses on the application of image processing technology to detect river water levels using CCTV cameras ...
Muhammad Akmal Ilmi   +2 more
doaj   +1 more source

YOLO-TS: A Lightweight YOLO Model for Traffic Sign Detection

open access: yesIEEE Access
Existing traffic sign detection algorithms suffer from high computational complexity and large parameter sizes, limiting their deployability. The YOLO-TS model integrates the Normalized Wasserstein Distance (NWD) with the Complete Intersection over Union (CIoU) loss function, significantly enhancing the detection of small traffic signs. The integration
Yunxiang Liu, Peng Luo
openaire   +2 more sources

Automated object detection based on YOLOv11 for monitoring benthic population dynamics: A new approach combining photogrammetry and open‐source GIS tools applied to sea cucumbers

open access: yesRemote Sensing in Ecology and Conservation, EarlyView.
This research established a new object detection model based on YOLOv11 to recognise benthic organisms, specifically sea cucumbers, by utilising high‐resolution photogrammetric‐based orthomosaics acquired along infralittoral Mediterranean Sea beds. The model demonstrated impressive performance metrics and, when combined with the Deepness plugin for the
Gian Mario Sangiovanni   +9 more
wiley   +1 more source

From snapshots to continuous estimates: Augmenting citizen science with computer vision for fish monitoring

open access: yesRemote Sensing in Ecology and Conservation, EarlyView.
This study presents an end‐to‐end computer‐vision pipeline for monitoring fish migration using underwater video. We integrate field camera deployment, annotation, model training and automated in‐season counting to generate continuous, high‐resolution data on river herring spawning migration.
Zhongqi Chen   +7 more
wiley   +1 more source

Deep Learning Based Traffic Sign Recognition Using YOLO Algorithm

open access: yesDüzce Üniversitesi Bilim ve Teknoloji Dergisi
Traffic sign detection has attracted a lot of attention in recent years among object recognition applications. Accurate and fast detection of traffic signs will also eliminate an important technical problem in autonomous vehicles.
Gökalp Çınarer
doaj   +1 more source

Deep learning‐based super‐resolution reconstruction and improved YOLOv9 for efficient benthos detection: a case study at Lake Hamana, Japan

open access: yesRemote Sensing in Ecology and Conservation, EarlyView.
This study presents a UAV‐based framework that integrates deep learning‐based super‐resolution reconstruction and an enhanced YOLO detector to improve centimetre‐scale benthic organism monitoring. Using hermit crabs in Lake Hamana, a coastal lagoon in Japan, as a case study, the method substantially enhanced small‐object detection performance ...
Fan Zhao   +10 more
wiley   +1 more source

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