Convolutional neural network: a review of models, methodologies and applications to object detection
A Dhillon, GK Verma - Progress in Artificial Intelligence, 2020 - Springer
Deep learning has developed as an effective machine learning method that takes in
numerous layers of features or representation of the data and provides state-of-the-art …
numerous layers of features or representation of the data and provides state-of-the-art …
Federated learning in mobile edge networks: A comprehensive survey
In recent years, mobile devices are equipped with increasingly advanced sensing and
computing capabilities. Coupled with advancements in Deep Learning (DL), this opens up …
computing capabilities. Coupled with advancements in Deep Learning (DL), this opens up …
DenseSPH-YOLOv5: An automated damage detection model based on DenseNet and Swin-Transformer prediction head-enabled YOLOv5 with attention mechanism
Objective. Computer vision-based up-to-date accurate damage classification and
localization are of decisive importance for infrastructure monitoring, safety, and the …
localization are of decisive importance for infrastructure monitoring, safety, and the …
WilDect-YOLO: An efficient and robust computer vision-based accurate object localization model for automated endangered wildlife detection
Objective. With climatic instability, various ecological disturbances, and human actions
threaten the existence of various endangered wildlife species. Therefore, an up-to-date …
threaten the existence of various endangered wildlife species. Therefore, an up-to-date …
A fast accurate fine-grain object detection model based on YOLOv4 deep neural network
Early identification and prevention of various plant diseases is a key feature of precision
agriculture technology. This paper presents a high-performance real-time fine-grain object …
agriculture technology. This paper presents a high-performance real-time fine-grain object …
Deep learning for unmanned aerial vehicle-based object detection and tracking: A survey
Owing to effective and flexible data acquisition, unmanned aerial vehicles (UAVs) have
recently become a hotspot across the fields of computer vision (CV) and remote sensing …
recently become a hotspot across the fields of computer vision (CV) and remote sensing …
Enhancing geometric factors in model learning and inference for object detection and instance segmentation
Deep learning-based object detection and instance segmentation have achieved
unprecedented progress. In this article, we propose complete-IoU (CIoU) loss and Cluster …
unprecedented progress. In this article, we propose complete-IoU (CIoU) loss and Cluster …
CNN-based transfer learning–BiLSTM network: A novel approach for COVID-19 infection detection
Abstract Coronavirus disease 2019 (COVID-2019), which emerged in Wuhan, China in 2019
and has spread rapidly all over the world since the beginning of 2020, has infected millions …
and has spread rapidly all over the world since the beginning of 2020, has infected millions …
Classification of monkeypox images based on transfer learning and the Al-Biruni Earth Radius Optimization algorithm
The world is still trying to recover from the devastation caused by the wide spread of COVID-
19, and now the monkeypox virus threatens becoming a worldwide pandemic. Although the …
19, and now the monkeypox virus threatens becoming a worldwide pandemic. Although the …
Object detection in optical remote sensing images: A survey and a new benchmark
Substantial efforts have been devoted more recently to presenting various methods for
object detection in optical remote sensing images. However, the current survey of datasets …
object detection in optical remote sensing images. However, the current survey of datasets …