Results 11 to 20 of about 11,225,352 (286)
Pixel-wise attention driven infrared small target detection network
Xibei Gongye Daxue XuebaoInfrared small target detection has been widely used in the military and civil fields. The detection difficulties lie in small target size, few details and complex background interference.
WANG Xiaolin +4 more
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MWIRSTD: A MWIR Small Target Detection Dataset [PDF]
2024 IEEE International Conference on Image Processing (ICIP)Accepted in ...
Nikhil Kumar +4 more
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Millimetre wave imaging for concealed target detection [PDF]
, 2011 PhDConcealed weapon detection (CWD) has been a hot topic as the concern about pub- lic safety increases. A variety of approaches for the detection of concealed objects on the human body based on earth magnetic ¯eld distortion, inductive magnetic ¯eld,
Zhang, Lianhong
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Micromachines, 2023 Space vehicles such as missiles and aircraft have relatively long tracking distances. Infrared (IR) detectors are used for small target detection. The target presents point target characteristics, which lack contour, shape, and texture information.
Juan Chen +6 more
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UAV Target Detection Algorithm Based on Improved YOLOv8
IEEE Access, 2023 Since UAVs usually fly at higher altitudes, resulting in a more significant proportion of small targets after imaging, this poses a challenge to the target detection algorithm at this stage; in addition, the high-speed flight of UAVs causes a sense of ...
Feng Wang +3 more
doaj +1 more source
CourtNet for Infrared Small-Target Detection
CoRR, 2022 Infrared small-target detection (ISTD) is an important computer vision task. ISTD aims at separating small targets from complex background clutter. The infrared radiation decays over distances, making the targets highly dim and prone to confusion with the background clutter, which makes the detector challenging to balance the precision and recall rate.
Jingchao Peng +4 more
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Discriminative Autoencoders for Small Targets Detection [PDF]
2014 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
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Remote 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
ECAP-YOLO: Efficient Channel Attention Pyramid YOLO for Small Object Detection in Aerial Image
Remote 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
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Vehicle detection in aerial imagery : A small target detection benchmark [PDF]
Journal 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 +3 more sources