The advent of deep learning has brought about more effective classification methods, utilizing Convolutional Neural Networks (CNN). However, existing CNN-based approaches primarily focus on either sailing or loitering movement patterns and struggle to capture valuable features and ...
(1)Trajectory Travel Time Estimation,典型的回归类问题,在模型最后接一个全连接层输出结果即可。 (2)Trajectory Classification,典型的多分类问题,在模型最后接一个全连接层,再加一个softmax输出结果即可。 (3)Trajectory Similarity,比较特殊,不需要微调,直接拿得到了两条轨迹的特征做欧氏距离比较即可。 Experiments ...
Systematically, we explore deep learning applications in trajectory management (pre-processing, storage, analysis, and visualization) and mining (trajectory-related forecasting, trajectory-related recommendation, trajectory classification, travel time estimation, anomaly detection, and mobility generation). ...
We evaluate our approach using Yonsei pedestrian trajectory data and Citi Bike datasets. The results show that the T-GCN prediction is more stable and better than other deep learning models. In addition, compared with other region division methods, the method of a top-down division of regions f...
Privacy-Preserving Classification on Deep Learning with Exponential Mechanism How to protect the privacy of training data in deep learning has been the subject of increasing amounts of related research in recent years. Private Aggreg... Q Ju,R Xia,S Li,... - 《International Journal of Computati...
visualizationbioinformaticsdeep-learninggenomicstabular-datasingle-cellbiomarker-discoveryclassification-algorithmbiomarkersbioinfomatics-pipelinegenomic-data-analysisgenomics-visualizationregression-algorithmsdata-classificationbioinformatics-tooltrajectory-inferencecell-annotationmulti-omic-integration ...
Krizhevsky A, Sutskever I, Hinton GE (2017) ImageNet classification with deep convolutional neural networks. Commun ACM 60(6):84–90. https://doi.org/10.1145/3065386 Article Google Scholar Li B, Mostafavi A (2022) Location intelligence reveals the extent, timing, and spatial variation of ...
[7] Saining Xie, Chen Sun, Jonathan Huang, Zhuowen Tu, and Kevin Murphy. Rethinking spatiotemporal feature learning: : Speed-accuracy trade-offs in video classification. In European Conference on Computer Vision (ECCV), 2018. [8] Du Tran, HengWang, Lorenzo Torresani, Jamie Ray, Yann LeCun...
May Petry, L., Leite Da Silva, C., Esuli, A., Renso, C., and Bogorny, V. (2020). MARC: a robust method for multiple-aspect trajectory classification via space, time, and semantic embeddings. International Journal of Geographical Information Science, 34(7), 1428-1450.Github ...
Like many machine learning applications, this approach uses both classification algorithms and regression algorithms to deal with the trajectory prediction problem. Using NGSIM (Next Generation Simulation) dataset and based on deep learning LSTM theory, Ling Huang et al. achieved self-vehicle lane ...