Evaluation of Automated Object-Detection Algorithms for Koala Detection in Infrared Aerial Imagery DOI Creative Commons
Laith A. H. Al-Shimaysawee, Anthony Finn, Delene Weber

et al.

Sensors, Journal Year: 2024, Volume and Issue: 24(21), P. 7048 - 7048

Published: Oct. 31, 2024

Effective detection techniques are important for wildlife monitoring and conservation applications especially helpful species that live in complex environments, such as arboreal animals like koalas (

Language: Английский

AI-Powered Cow Detection in Complex Farm Environments DOI Creative Commons
Voncarlos M. Araújo,

Ines Rili,

Thomas Gisiger

et al.

Smart Agricultural Technology, Journal Year: 2025, Volume and Issue: unknown, P. 100770 - 100770

Published: Jan. 1, 2025

Language: Английский

Citations

1
Transmission Line Bolt Missing Detection Based on Improved YOLOv8 Network DOI

Shounan Bao,

Chaofeng Li

Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 257 - 273

Published: Jan. 1, 2025

Language: Английский

Citations

0
Innovative Deep Learning Image Technologies DOI
Muhammad Akram, Sibghat Ullah Bazai, Muhammad Sulaman

et al.

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 145 - 180

Published: March 7, 2025

The chapter gives an overview of the applications deep learning and image processing in different industries medicine, automobiles, entertainment, security. Multiple advanced techniques such as CNN, GAN, ViT that have become handy analysis processing. From medical diagnostics to autonomous vehicles, environmental monitoring, surveillance, its show impact on accuracy efficiency. It also discusses critical ethical issues, data privacy, model biases, energy consumption, points out some possible solutions reduce those effects. In general, this contribution provides a advances related by potential for further innovative developments wide range applications.

Language: Английский

Citations

0
Accelerating ecosystem monitoring through computer vision with deep metric learning DOI Creative Commons
Yurika Oba, Hideyuki Doi

Ecological Complexity, Journal Year: 2025, Volume and Issue: 62, P. 101124 - 101124

Published: May 9, 2025

Language: Английский

Citations

0
SGW-YOLOv8n: An Improved YOLOv8n-Based Model for Apple Detection and Segmentation in Complex Orchard Environments DOI Creative Commons

Tao Wu,

Zhonghua Miao,

Weichao Huang

et al.

Agriculture, Journal Year: 2024, Volume and Issue: 14(11), P. 1958 - 1958

Published: Oct. 31, 2024

This study addresses the problem of detecting occluded apples in complex unstructured environments orchards and proposes an apple detection segmentation model based on improved YOLOv8n-SGW-YOLOv8n. The improves by combining SPD-Conv convolution module, GAM global attention mechanism, Wise-IoU loss function, which enhances accuracy robustness. module preserves fine-grained features image converting spatial information into channel information, is particularly suitable for small target detection. mechanism recognition targets strengthening feature representation dimensions. function further optimises regression frame. Finally, pre-prepared dataset used training validation. results show that SGW-YOLOv8n significantly relative to original YOLOv8n instance tasks, especially occlusion scenes. mAP 75.9% 75.7% maintains a processing speed 44.37 FPS, can meet real-time requirements, providing effective technical support fruits fruit harvesting robots.

Language: Английский

Citations

2
Wildlife target detection based on improved YOLOX-s network DOI Creative Commons
Xiaoan Bao,

Zhou LinQing,

Tu XiaoMei

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Oct. 9, 2024

To addresse the problem of poor detection accuracy or even false wildlife caused by rainy environment at night. In this paper, a target algorithm based on improved YOLOX-s network is proposed. Our comprises MobileViT-Pooling module, Dynamic Head and Focal-IoU module.First, module introduced.It MobileViT attention mechanism, which uses spatial pooling operator with no parameters as token mixer to reduce number parameters. This performs feature extraction three layers backbone output respectively, senses global information strengthens weight effective information. Second, used downstream task detection, fuses scale sensing, sensing improves representation ability head. Lastly, Focal idea utilized improve IoU loss function, balances learning high low quality for network. Experimental results reveal that our achieves notable performance boost [email protected] reaching 87.8% (an improvement 7.9%) [email protected]:0.95 62.0% 5.3%). advancement significantly augments night-time under conditions, concurrently diminishing detections in such challenging environments.

Language: Английский

Citations

0
Evaluation of Automated Object-Detection Algorithms for Koala Detection in Infrared Aerial Imagery DOI Creative Commons
Laith A. H. Al-Shimaysawee, Anthony Finn, Delene Weber

et al.

Sensors, Journal Year: 2024, Volume and Issue: 24(21), P. 7048 - 7048

Published: Oct. 31, 2024

Effective detection techniques are important for wildlife monitoring and conservation applications especially helpful species that live in complex environments, such as arboreal animals like koalas (

Language: Английский

Citations

0