Results 151 to 160 of about 558,332 (197)

UAV-DETR: Efficient End-to-End Object Detection for Unmanned Aerial Vehicle Imagery

IEEE/RJS International Conference on Intelligent RObots and Systems
Unmanned aerial vehicle object detection (UAV-OD) has been widely used in various scenarios. However, most existing UAV-OD algorithms rely on manually designed components, which require extensive tuning.
Huaxiang Zhang, Kai Liu, Zhongxue Gan, Guo-Niu Zhu   +3 more
semanticscholar   +1 more source

YoloOW: A Spatial Scale Adaptive Real-Time Object Detection Neural Network for Open Water Search and Rescue From UAV Aerial Imagery

IEEE Transactions on Geoscience and Remote Sensing
Personnel and boat detection in unmanned aerial vehicles (UAVs) imagery plays a crucial role in open water search and rescue missions. The diverse perspectives and altitudes of UAV images often result in significant variations in the imagery’s appearance
Jianhao Xu, Xiangtao Fan, Hongdeng Jian, Chen Xu, Weijia Bei, Qifeng Ge, Teng Zhao   +6 more
semanticscholar   +1 more source

Near-Field High-Resolution Maps of the Ridgecrest Earthquakes from Aerial Imagery

Seismological Research Letters, 2021
High-resolution maps of surface rupturing earthquakes are essential tools for quantifying rupture hazard, understanding the mechanics of rupture propagation, and interpreting evidence of past earthquakes in the landscape.
A. R. Rodriguez Padilla, Mercedes A. Quintana, Ruth M. Prado, Brian J. Aguilar, T. Shea, M. Oskin, Leslie Garcia   +6 more
semanticscholar   +1 more source

Multi-Class Vehicle Detection and Classification with YOLO11 on UAV-Captured Aerial Imagery

2024 IEEE 7th International Conference on Actual Problems of Unmanned Aerial Vehicles Development (APUAVD)
Aerial imaging and object detection using unmanned aerial vehicle (UAV) systems pose unique challenges, including varying altitudes, dynamic backgrounds, and changes in lighting and weather conditions.
Murat Bakirci, Petro Dmytrovych, I. Bayraktar, Oleh Anatoliyovych   +3 more
semanticscholar   +1 more source

Rule-Based Interpretation of Aerial Imagery

IEEE Transactions on Pattern Analysis and Machine Intelligence, 1985
In this paper, we describe the organization of a rule-based system, SPAM, that uses map and domain-specific knowledge to interpret airport scenes. This research investigates the use of a rule-based system for the control of image processing and interpretation of results with respect to a world model, as well as the representation of the world model ...
D M, McKeown, W A, Harvey, J, McDermott
openaire   +2 more sources

MSANet: Multiscale Self-Attention Aggregation Network for Few-Shot Aerial Imagery Segmentation

IEEE Transactions on Geoscience and Remote Sensing
Few-shot aerial imagery segmentation refers to the task of segmenting specific objects in scenes that have not been encountered during training with a small amount of annotated data for reference.
Jianzhao Li, Maoguo Gong, Weihao Li, Mingyang Zhang, Yourun Zhang, Shanfeng Wang, Yue Wu   +6 more
semanticscholar   +1 more source

Traffic data collection from aerial imagery

Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems, 2003
Abstract This paper describes a new data collection system prototype for determining individual vehicle trajectories from sequences of digital aerial images. The software was tested on data collected from a helicopter, using a digital camera gathering highresolution monochrome images.
S.P. Hoogendoorn, H.J. Van Zuylen, M. Schreuder, B. Gorte, G. Vosselman   +4 more
openaire   +1 more source

Convolutional neural networks for object detection in aerial imagery for disaster response and recovery

Advanced Engineering Informatics, 2020
Accurate and timely access to data describing disaster impact and extent of damage is key to successful disaster management (a process that includes prevention, mitigation, preparedness, response, and recovery). Airborne data acquisition using helicopter
Yalong Pi, Nipun D. Nath, A. Behzadan
semanticscholar   +1 more source

Yield estimation of soybean breeding lines under drought stress using unmanned aerial vehicle-based imagery and convolutional neural network

, 2021
Crop yield is a primary trait to select superior genotypes and evaluate breeding efficiency in breeding programs. Crops with high yield potential are usually selected from numerous breeding lines in multiple years and locations.
Jing Zhou, Jianfeng Zhou, Heng Ye, Md. Liakat Ali, Pengyin Chen, H. Nguyen   +5 more
semanticscholar   +1 more source

Geolocation of aerial imagery

SPIE Proceedings, 2004
Geolocation error in aerial imagery can arise from many sources. This paper catalogs the major sources and shows how residual error may be reduced still further through the use of ground control points.
openaire   +1 more source