[HTML][HTML] A review of practical ai for remote sensing in earth sciences

B Janga, GP Asamani, Z Sun, N Cristea - Remote Sensing, 2023 - mdpi.com
Integrating Artificial Intelligence (AI) techniques with remote sensing holds great potential for
revolutionizing data analysis and applications in many domains of Earth sciences. This …

[HTML][HTML] In-depth review of yolov1 to yolov10 variants for enhanced photovoltaic defect detection

M Hussain, R Khanam - Solar, 2024 - mdpi.com
This review presents an investigation into the incremental advancements in the YOLO (You
Only Look Once) architecture and its derivatives, with a specific focus on their pivotal …

[HTML][HTML] Object detection in adverse weather for autonomous driving through data merging and YOLOv8

D Kumar, N Muhammad - Sensors, 2023 - mdpi.com
For autonomous driving, perception is a primary and essential element that fundamentally
deals with the insight into the ego vehicle's environment through sensors. Perception is …

[HTML][HTML] Analysis of Stable Diffusion-derived fake weeds performance for training Convolutional Neural Networks

H Moreno, A Gómez, S Altares-López, A Ribeiro… - … and Electronics in …, 2023 - Elsevier
Weeds challenge crops by competing for resources and spreading diseases, impacting crop
yield and quality. Effective weed detection can enhance herbicide application, thus reducing …

[HTML][HTML] Fire detection and notification method in ship areas using deep learning and computer vision approaches

K Avazov, MK Jamil, B Muminov, AB Abdusalomov… - Sensors, 2023 - mdpi.com
Fire incidents occurring onboard ships cause significant consequences that result in
substantial effects. Fires on ships can have extensive and severe wide-ranging impacts on …

[HTML][HTML] Using an improved lightweight YOLOv8 model for real-time detection of multi-stage apple fruit in complex orchard environments

B Ma, Z Hua, Y Wen, H Deng, Y Zhao, L Pu… - Artificial Intelligence in …, 2024 - Elsevier
For the purpose of monitoring apple fruits effectively throughout the entire growth period in
smart orchards. A lightweight model named YOLOv8n-ShuffleNetv2-Ghost-SE was …

[HTML][HTML] Evaluation of YOLO object detectors for weed detection in different turfgrass scenarios

M Sportelli, OE Apolo-Apolo, M Fontanelli, C Frasconi… - Applied Sciences, 2023 - mdpi.com
The advancement of computer vision technology has allowed for the easy detection of
weeds and other stressors in turfgrasses and agriculture. This study aimed to evaluate the …

FSDF: A high-performance fire detection framework

H Zhao, J Jin, Y Liu, Y Guo, Y Shen - Expert Systems with Applications, 2024 - Elsevier
Fire detection is crucial in the protection of human life and property. Traditional
methodologies and deep learning techniques have been extensively employed in this area …

[HTML][HTML] Tassel-YOLO: A new high-precision and real-time method for maize tassel detection and counting based on UAV aerial images

H Pu, X Chen, Y Yang, R Tang, J Luo, Y Wang, J Mu - Drones, 2023 - mdpi.com
Tassel is an important part of the maize plant. The automatic detection and counting of
tassels using unmanned aerial vehicle (UAV) imagery can promote the development of …

[HTML][HTML] Research on improved yolov5 for low-light environment object detection

J Wang, P Yang, Y Liu, D Shang, X Hui, J Song… - Electronics, 2023 - mdpi.com
Object detection in low-light scenarios has been widely acknowledged as a significant
research area in the field of computer vision, presenting a challenging task. Aiming at the …