Deep learning-based object detection in maritime unmanned aerial vehicle imagery: Review and experimental comparisons
With the advancement of maritime unmanned aerial vehicles (UAVs) and deep learning
technologies, the application of UAV-based object detection has become increasingly …
technologies, the application of UAV-based object detection has become increasingly …
Yolov7-sea: Object detection of maritime uav images based on improved yolov7
H Zhao, H Zhang, Y Zhao - Proceedings of the IEEE/CVF …, 2023 - openaccess.thecvf.com
Object detection algorithms play an important role in maritime search and rescue missions,
where they are designed to detect people, boats and other objects in open water. However …
where they are designed to detect people, boats and other objects in open water. However …
Multi-object tracking meets moving UAV
Multi-object tracking in unmanned aerial vehicle (UAV) videos is an important vision task
and can be applied in a wide range of applications. However, conventional multi-object …
and can be applied in a wide range of applications. However, conventional multi-object …
A novel tensor decomposition-based efficient detector for low-altitude aerial objects with knowledge distillation scheme
Unmanned aerial vehicles (UAVs) have gained significant attention in practical applications,
especially the low-altitude aerial (LAA) object detection imposes stringent requirements on …
especially the low-altitude aerial (LAA) object detection imposes stringent requirements on …
A guide to image and video based small object detection using deep learning: Case study of maritime surveillance
Small object detection (SOD) in optical images and videos is a challenging problem that
even state-of-the-art generic object detection methods fail to accurately localize and identify …
even state-of-the-art generic object detection methods fail to accurately localize and identify …
Leveraging synthetic data in object detection on unmanned aerial vehicles
Acquiring data to train deep learning-based object detectors on Unmanned Aerial Vehicles
(UAVs) is expensive, time-consuming and may even be prohibited by law in specific …
(UAVs) is expensive, time-consuming and may even be prohibited by law in specific …
RingMo-sense: Remote sensing foundation model for spatiotemporal prediction via spatiotemporal evolution disentangling
F Yao, W Lu, H Yang, L Xu, C Liu, L Hu… - … on Geoscience and …, 2023 - ieeexplore.ieee.org
Remote sensing (RS) spatiotemporal prediction aims to infer future trends from historical
spatiotemporal data, eg, videos and time-series images, which has a broad application …
spatiotemporal data, eg, videos and time-series images, which has a broad application …
Mcuformer: Deploying vision tranformers on microcontrollers with limited memory
Due to the high price and heavy energy consumption of GPUs, deploying deep models on
IoT devices such as microcontrollers makes significant contributions for ecological AI …
IoT devices such as microcontrollers makes significant contributions for ecological AI …
[HTML][HTML] Poseidon: A data augmentation tool for small object detection datasets in maritime environments
Certain fields present significant challenges when attempting to train complex Deep
Learning architectures, particularly when the available datasets are limited and imbalanced …
Learning architectures, particularly when the available datasets are limited and imbalanced …
1st workshop on maritime computer vision (macvi) 2023: Challenge results
Abstract The 1st Workshop on Maritime Computer Vision (MaCVi)| 2023 focused on
maritime computer vision for Unmanned| Aerial Vehicles (UAV) and Unmanned Surface …
maritime computer vision for Unmanned| Aerial Vehicles (UAV) and Unmanned Surface …