Harwood, D.A.,
Chang, S., and
Davis, L.S.,
Interpreting Aerial Photographs by Segmentation and Search,
DARPA87(507-520).
See also Sigma Image Understanding System, The. Find segments (homogeneous regions), then find instances which
satisfy definitions of object types, then search for support, then
improve instances, then iterate with new estimates of parameters.
See also Fua and Leclerc Guided Segmentation Papers.
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2406
Task analysis, Head, Semantics, Object detection, Fuses, Urban areas,
Remote sensing, Dynamic convolution, peripheral points,
salient instance segmentation (SIS)
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A Lightweight Object Counting Network Based on Density Map Knowledge
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2502
Feature extraction, Knowledge engineering, Accuracy,
Remote sensing, Image reconstruction, Convolution, multi-scale
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Wu, H.L.[Hong-Lin],
Zeng, Z.B.[Zhao-Bin],
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MCFNet: Multiscale Cross-Modal Fusion Network for Remote Sensing
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SPLetters(32), 2025, pp. 2758-2762.
IEEE DOI
2508
Feature extraction, Remote sensing, Semantic segmentation, Convolution,
Training, Micromechanical devices, Decoding, semantic segmentation
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Verdonck, L.[Lieven],
Dabas, M.[Michel],
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Interactive, Shallow Machine Learning-Based Semantic Segmentation of
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Darji, D.,
Vejarano, G.,
Counting Static Targets Using an Unmanned Aerial Vehicle On-the-Fly
and Autonomously,
CRV18(206-213)
IEEE DOI
1812
Cameras, Automobiles, Unmanned aerial vehicles, Trajectory, Roads,
Portable computers, Target tracking, unmanned aerial vehicle,
target counting
BibRef
Hsieh, M.R.,
Lin, Y.L.,
Hsu, W.H.,
Drone-Based Object Counting by Spatially Regularized Regional
Proposal Network,
ICCV17(4165-4173)
IEEE DOI
1802
SLAM (robots), automobiles, autonomous aerial vehicles, cameras,
mobile robots, object detection, robot vision, LPNs,
Videos
BibRef
Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Segment Anything Model .