Object detection using YOLO: Challenges, architectural successors, datasets and applications
Object detection is one of the predominant and challenging problems in computer vision.
Over the decade, with the expeditious evolution of deep learning, researchers have …
Over the decade, with the expeditious evolution of deep learning, researchers have …
Machine learning and landslide studies: recent advances and applications
Upon the introduction of machine learning (ML) and its variants, in the form that we know
today, to the landslide community, many studies have been carried out to explore the …
today, to the landslide community, many studies have been carried out to explore the …
A survey of machine learning and deep learning in remote sensing of geological environment: Challenges, advances, and opportunities
Due to limited resources and environmental pollution, monitoring the geological
environment has become essential for many countries' sustainable development. As various …
environment has become essential for many countries' sustainable development. As various …
[HTML][HTML] Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran
The identification of landslide-prone areas is an essential step in landslide hazard
assessment and mitigation of landslide-related losses. In this study, we applied two novel …
assessment and mitigation of landslide-related losses. In this study, we applied two novel …
Evaluation of different machine learning methods and deep-learning convolutional neural networks for landslide detection
There is a growing demand for detailed and accurate landslide maps and inventories
around the globe, but particularly in hazard-prone regions such as the Himalayas. Most …
around the globe, but particularly in hazard-prone regions such as the Himalayas. Most …
A spatially explicit deep learning neural network model for the prediction of landslide susceptibility
With the increasing threat of recurring landslides, susceptibility maps are expected to play a
bigger role in promoting our understanding of future landslides and their magnitude. This …
bigger role in promoting our understanding of future landslides and their magnitude. This …
Application of convolutional neural networks featuring Bayesian optimization for landslide susceptibility assessment
This study developed a deep learning based technique for the assessment of landslide
susceptibility through a one-dimensional convolutional network (1D-CNN) and Bayesian …
susceptibility through a one-dimensional convolutional network (1D-CNN) and Bayesian …
Statistical analysis of design aspects of various YOLO-based deep learning models for object detection
Object detection is a critical and complex problem in computer vision, and deep neural
networks have significantly enhanced their performance in the last decade. There are two …
networks have significantly enhanced their performance in the last decade. There are two …
In-depth review of yolov1 to yolov10 variants for enhanced photovoltaic defect detection
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 …
Only Look Once) architecture and its derivatives, with a specific focus on their pivotal …
Landslide mapping with remote sensing: challenges and opportunities
Landslide mapping is the primary step for landslide investigation and prevention. At present,
both the accuracy and the degree of automation of landslide mapping with remote sensing …
both the accuracy and the degree of automation of landslide mapping with remote sensing …