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High-order local ternary patterns with locality preserving projection for smoke detection and image classification.

, , , , , and . Inf. Sci., (2016)

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Mixed co-occurrence of local binary patterns and Hamming-distance-based local binary patterns., , and . Inf. Sci., (2018)Dual-Encoded Features from Both Spatial and Curvelet Domains for Image Smoke Recognition., , , , and . TIIS, 13 (4): 2078-2093 (2019)Convolutional neural networks based on multi-scale additive merging layers for visual smoke recognition., , , , and . Mach. Vis. Appl., 30 (2): 345-358 (2019)Fusing texture, edge and line features for smoke recognition., , , , and . IET Image Processing, 13 (14): 2805-2812 (2019)High-order local ternary patterns with locality preserving projection for smoke detection and image classification., , , , , and . Inf. Sci., (2016)Holistic learning-based high-order feature descriptor for smoke recognition., , and . IJWMIP, 17 (2): 1940005 (2019)Co-occurrence matching of local binary patterns for improving visual adaption and its application to smoke recognition., , , , and . IET Comput. Vis., 13 (2): 178-187 (2019)Encoding pairwise Hamming distances of Local Binary Patterns for visual smoke recognition., , , , and . Computer Vision and Image Understanding, (2019)Learning multi-scale and multi-order features from 3D local differences for visual smoke recognition., , , , and . Inf. Sci., (2018)Sub Oriented Histograms of Local Binary Patterns for Smoke Detection and Texture Classification., , , , , and . TIIS, 10 (4): 1807-1823 (2016)