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Powerline Detection and Characterization in General-Purpose Airborne LiDAR Surveys.

, , , , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2024)

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Pixel parallel vessel tree extraction for a personal authentication system., , , and . ISCAS, page 1596-1599. IEEE, (2008)Design of multilayer discrete time cellular neural networks for image processing tasks based on genetic algorithms., , and . ISCAS, page 133-136. IEEE, (2000)Feature detection and matching on an SIMD/MIMD hybrid embedded processor., , and . CVPR Workshops, page 21-26. IEEE Computer Society, (2012)Pixel-Level Snakes., , , and . ICPR, page 1640-1643. IEEE Computer Society, (2000)A one-quadrant discrete-time cellular neural network architecture for pixel-level snakes: B/W processing., , , , and . ISCAS (4), page 3922-3925. IEEE, (2005)Powerline Detection and Characterization in General-Purpose Airborne LiDAR Surveys., , , , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2024)Application of a Multilayer Discrete-Time CNN to Deformable Models., , , and . IWANN, volume 1240 of Lecture Notes in Computer Science, page 1193-1202. Springer, (1997)Performance analysis of massively parallel embedded hardware architectures for retinal image processing., , , and . EURASIP J. Image Video Process., (2011)A mixed-signal CMOS DTCNN chip for pixel-level snakes., , and . ISCAS (5), page 465-468. IEEE, (2004)A digital cellular-based system for retinal vessel-tree extraction., , , , and . ECCTD, page 835-838. IEEE, (2009)