Yolo-based uav technology: A review of the research and its applications
C Chen, Z Zheng, T Xu, S Guo, S Feng, W Yao, Y Lan - Drones, 2023 - mdpi.com
In recent decades, scientific and technological developments have continued to increase in
speed, with researchers focusing not only on the innovation of single technologies but also …
speed, with researchers focusing not only on the innovation of single technologies but also …
[HTML][HTML] Application of deep learning and machine learning models to detect COVID-19 face masks-A review
E Mbunge, S Simelane, SG Fashoto… - Sustainable Operations …, 2021 - Elsevier
The continuous COVID-19 upsurge and emerging variants present unprecedented
challenges in many health systems. Many regulatory authorities have instituted the …
challenges in many health systems. Many regulatory authorities have instituted the …
Evaluation of robust spatial pyramid pooling based on convolutional neural network for traffic sign recognition system
Traffic sign recognition (TSR) is a noteworthy issue for real-world applications such as
systems for autonomous driving as it has the main role in guiding the driver. This paper …
systems for autonomous driving as it has the main role in guiding the driver. This paper …
UIT-ADrone: A novel drone dataset for traffic anomaly detection
Anomaly detection plays an increasingly important role in video surveillance and is one of
the issues that have attracted various communities, such as computer vision, machine …
the issues that have attracted various communities, such as computer vision, machine …
A low-cost UAV framework towards ornamental plant detection and counting in the wild
Object detection still keeps its role as one of the fundamental challenges within the computer
vision territory. In particular, achieving satisfying results concerning object detection from …
vision territory. In particular, achieving satisfying results concerning object detection from …
From machine learning to deep learning in agriculture–the quantitative review of trends
In the last two decades, we have witnessed the intensive development of artificial
intelligence in the field of agriculture. In this period, the transition from the application of …
intelligence in the field of agriculture. In this period, the transition from the application of …
Real-time droplet detection for agricultural spraying systems: A deep learning approach
Nozzles are ubiquitous in agriculture: they are used to spray and apply nutrients and
pesticides to crops. The properties of droplets sprayed from nozzles are vital factors that …
pesticides to crops. The properties of droplets sprayed from nozzles are vital factors that …
Predicting clinical outcome in acute ischemic stroke using parallel multi-parametric feature embedded Siamese network
Stroke is the second leading cause of death and disability worldwide, with ischemic stroke
as the most common type. The preferred diagnostic procedure at the acute stage is the …
as the most common type. The preferred diagnostic procedure at the acute stage is the …
Analysis of YOLOv5 and DeepLabv3+ algorithms for detecting illegal cultivation on public land: A case study of a riverside in Korea
K Lee, B Wang, S Lee - … Journal of Environmental Research and Public …, 2023 - mdpi.com
Rivers are generally classified as either national or local rivers. Large-scale national rivers
are maintained through systematic maintenance and management, whereas many …
are maintained through systematic maintenance and management, whereas many …
Comparison of faster r-cnn and yolov5 for overlapping objects recognition
Classifying an overlapping object is one of the main challenges faced by researchers who
work in object detection and recognition. Most of the available algorithms that have been …
work in object detection and recognition. Most of the available algorithms that have been …