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Discovering Fine-Grained Spatial Pattern From Taxi Trips: Where Point Process Meets Matrix Decomposition and Factorization.

, , , , , , and . IEEE Trans. Intell. Transp. Syst., 19 (10): 3208-3219 (2018)

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Online dictionary learning for Local Coordinate Coding with Locality Coding Adaptors., , , , , , and . Neurocomputing, (2015)Undoing the codebook bias by linear transformation with sparsity and F-norm constraints for image classification., , , , , , and . Pattern Recognit. Lett., (2014)Pedestrian detection via logistic multiple instance boosting., , , and . ICIP, page 1464-1467. IEEE, (2008)Interactive event detection in crowd scenes., , , and . ICIMCS, page 46-49. ACM, (2012)A Channel-ensemble Approach: Unbiased and Low-variance Pseudo-labels is Critical for Semi-supervised Classification., , , and . CoRR, (2024)Modeling Multi-Granularity Context Information Flow for Pavement Crack Detection., , and . CoRR, (2024)Justify role of Similarity Diffusion Process in cross-media topic ranking: an empirical evaluation., , , , and . Multim. Tools Appl., 76 (23): 25145-25157 (2017)Unsupervised Pixel-level Crack Detection Based on Generative Adversarial Network., , , and . ICMSSP, page 6-10. ACM, (2020)Multiple Instance Boost Using Graph Embedding Based Decision Stump for Pedestrian Detection., , and . ECCV (4), volume 5305 of Lecture Notes in Computer Science, page 541-552. Springer, (2008)Treat samples differently: Object tracking with semi-supervised online CovBoost., , , , and . ICCV, page 627-634. IEEE Computer Society, (2011)