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 …
Deep long-tailed learning: A survey
Deep long-tailed learning, one of the most challenging problems in visual recognition, aims
to train well-performing deep models from a large number of images that follow a long-tailed …
to train well-performing deep models from a large number of images that follow a long-tailed …
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 …
Pavement crack detection based on transformer network
Accurate pavement surface crack detection is essential for pavement assessment and
maintenance. This study aims to improve pavement crack detection under noisy conditions …
maintenance. This study aims to improve pavement crack detection under noisy conditions …
A survey on long-tailed visual recognition
L Yang, H Jiang, Q Song, J Guo - International Journal of Computer Vision, 2022 - Springer
The heavy reliance on data is one of the major reasons that currently limit the development
of deep learning. Data quality directly dominates the effect of deep learning models, and the …
of deep learning. Data quality directly dominates the effect of deep learning models, and the …
VisDrone-DET2021: The vision meets drone object detection challenge results
Object detection on the drone faces a great diversity of challenges such as small object
inference, background clutter and wide viewpoint. In contrast to traditional detection problem …
inference, background clutter and wide viewpoint. In contrast to traditional detection problem …
Ace: Ally complementary experts for solving long-tailed recognition in one-shot
One-stage long-tailed recognition methods improve the overall performance in a" seesaw"
manner, ie, either sacrifice the head's accuracy for better tail classification or elevate the …
manner, ie, either sacrifice the head's accuracy for better tail classification or elevate the …
mSODANet: A network for multi-scale object detection in aerial images using hierarchical dilated convolutions
V Chalavadi, P Jeripothula, R Datla, SB Ch - Pattern Recognition, 2022 - Elsevier
The object detection in aerial images is one of the most commonly used tasks in the wide-
range of computer vision applications. However, the object detection is more challenging …
range of computer vision applications. However, the object detection is more challenging …
Tph-yolov5++: Boosting object detection on drone-captured scenarios with cross-layer asymmetric transformer
Object detection in drone-captured images is a popular task in recent years. As drones
always navigate at different altitudes, the object scale varies considerably, which burdens …
always navigate at different altitudes, the object scale varies considerably, which burdens …
Prototype-CNN for few-shot object detection in remote sensing images
Recently, due to the excellent representation ability of convolutional neural networks
(CNNs), object detection in remote sensing images has undergone remarkable …
(CNNs), object detection in remote sensing images has undergone remarkable …