Results 11 to 20 of about 1,075,591 (257)

SegDetector: A Deep Learning Model for Detecting Small and Overlapping Damaged Buildings in Satellite Images

open access: yesRemote Sensing, 2022
Buildings bear much of the damage from natural disasters, and determining the extent of this damage is of great importance to post-disaster emergency relief.
Zhengbo Yu   +7 more
doaj   +1 more source

Lightweight SM-YOLOv5 Tomato Fruit Detection Algorithm for Plant Factory

open access: yesSensors, 2023
Due to their rapid development and wide application in modern agriculture, robots, mobile terminals, and intelligent devices have become vital technologies and fundamental research topics for the development of intelligent and precision agriculture ...
Xinfa Wang   +6 more
doaj   +1 more source

ECAP-YOLO: Efficient Channel Attention Pyramid YOLO for Small Object Detection in Aerial Image

open access: yesRemote Sensing, 2021
Detection of small targets in aerial images is still a difficult problem due to the low resolution and background-like targets. With the recent development of object detection technology, efficient and high-performance detector techniques have been ...
Munhyeong Kim, Jongmin Jeong, Sungho Kim
doaj   +1 more source

Small moving targets detection using outlier detection algorithms [PDF]

open access: yesSPIE Proceedings, 2010
Recent research in motion detection has shown that various outlier detection methods could be used for efficient detection of small moving targets. These algorithms detect moving objects as outliers in a properly defined attribute space, where outlier is defined as an object distinct from the objects in its neighborhood.
Natasa Reljin   +6 more
openaire   +1 more source

YOLOv3_ReSAM: A Small-Target Detection Method

open access: yesElectronics, 2022
Small targets in long-distance aerial photography have the problems of small size and blurry appearance, and traditional object detection algorithms face great challenges in the field of small-object detection. With the collection of massive data in the information age, traditional object detection algorithms have been gradually replaced by deep ...
Bailin Liu   +3 more
openaire   +1 more source

Infrared Small Maritime Target Detection Based on Integrated Target Saliency Measure

open access: yesIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Robust and effective detection of a small target in an infrared maritime image is a key technology of maritime target search and tracking applications. Infrared small target detection is a challenging task due to the factors such as dim small targets and
Ping Yang, Lili Dong, Wenhai Xu
doaj   +1 more source

Vehicle detection in aerial imagery : A small target detection benchmark [PDF]

open access: yesJournal of Visual Communication and Image Representation, 2016
This paper introduces VEDAI: Vehicle Detection in Aerial Imagery a new database of aerial images provided as a tool to benchmark automatic target recognition algorithms in unconstrained environments. The vehicles contained in the database, in addition of being small, exhibit different variabil-ities such as multiple orientations, lighting/shadowing ...
Razakarivony, Sébastien   +1 more
openaire   +2 more sources

Small Target Detection Based on Improved SSD Algorithm [PDF]

open access: yesJisuanji gongcheng, 2023
SSD is a classical single-stage target detection algorithm that makes prediction by generating six scale feature maps on different convolutional layers.
Shan WU, Feng ZHOU
doaj   +1 more source

A Small Target Detection Method Based on Deep Learning With Considerate Feature and Effectively Expanded Sample Size

open access: yesIEEE Access, 2021
As a basic task in the field of computer vision, target detection has been concerned by many researchers. The performance of target detection method is also directly related to the research in many advanced semantic fields.
Jun Zhang, Yizhen Meng, Zhipeng Chen
doaj   +1 more source

Discriminative Autoencoders for Small Targets Detection [PDF]

open access: yes2014 22nd International Conference on Pattern Recognition, 2014
This paper introduces the new concept of discriminative autoencoders. In contrast with the standard autoencoders -- which are artificial neural networks used to learn compressed representation for a set of data -- discriminative autoencoders aim at learning low-dimensional discriminant encodings using two classes of data (denoted such as the positive ...
Razakarivony, Sebastien   +1 more
openaire   +2 more sources

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