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Color space selection for self-organizing map based foreground detection in video sequences.

, , , , and . IJCNN, page 3347-3354. IEEE, (2014)

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Improved detection of small objects in road network sequences using CNN and super resolution., , and . Expert Syst. J. Knowl. Eng., (2022)A Competitive Neural Network for Multiple Object Tracking in Video Sequence Analysis., , , , and . Neural Process. Lett., 37 (1): 47-67 (2013)Deep learning-based super-resolution of 3D magnetic resonance images by regularly spaced shifting., , , , and . Neurocomputing, (2020)Object detection in traffic videos: an optimized approach using super-resolution and maximal clique algorithm., , , and . Neural Comput. Appl., 35 (26): 18999-19013 (September 2023)Neural controller for PTZ cameras based on nonpanoramic foreground detection., , , , and . IJCNN, page 404-411. IEEE, (2017)Small-Scale Urban Object Anomaly Detection Using Convolutional Neural Networks with Probability Estimation., , , and . Sensors, 23 (16): 7185 (August 2023)Pixel Features for Self-organizing Map Based Detection of Foreground Objects in Dynamic Environments., , , , and . SOCO-CISIS-ICEUTE, volume 527 of Advances in Intelligent Systems and Computing, page 247-255. (2016)Foreground Detection Enhancement Using Pearson Correlation Filtering., , , and . IPMU (3), volume 855 of Communications in Computer and Information Science, page 417-428. Springer, (2018)Machine learning models to search relevant genetic signatures in clinical context., , , , and . IJCNN, page 1649-1656. IEEE, (2017)Aggregation of Convolutional Neural Network Estimations of Homographies by Color Transformations of the Inputs., , , and . IEEE Access, (2020)