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Table 5 Bibliographic summary of papers in IEEE Xplore

From: Intelligent video surveillance: a review through deep learning techniques for crowd analysis

Document title Publication_Year Funding information
Sparse coding guided spatiotemporal feature learning for abnormal event detection in large videos [53] 2019 National Nature Science Foundation of China; National Youth Top-notch Talent Support Program
Rejecting motion outliers for efficient crowd anomaly detection [54] 2019 Ministry of Science, ICT and Future Planning
Deep multi-view feature learning for person re-identification [55] 2018 National Natural Science Foundation of China; Yunnan Natural Science Funds; Guangdong Natural Science Funds; Yunnan University
Image-to-video person re-identification with temporally memorized similarity learning [56] 2018 National Natural Science Foundation of China; NSFC-Shenzhen Robotics Projects; Natural Science Foundation of Guangdong Province; Fundamental Research Funds for the Central Universities; ZTE Corporation
Fight recognition in video using hough forests and 2D convolutional neural network [57] 2018 Ministerio de EconomÃa y Competitividad
Anomalous sound detection using deep audio representation and a BLSTM network for audio surveillance of roads [58] 2018 National Natural Science Foundation of China; National Laboratory of Pattern Recognition
Convolutional neural networks based fire detection in surveillance videos [59] 2018 National Research Foundation of Korea (NRF); Korea government (MSIP)
Action recognition in video sequences using deep bi-directional LSTM with CNN features [60] 2018 National Research Foundation of Korea Grant; Korea Government (MSIP)
A deep spatiotemporal perspective for understanding crowd behavior [61] 2018  
Road traffic conditions classification based on multilevel filtering of image content using convolutional neural networks [62] 2018  
Indoor person identification using a low-power FMCW radar [63] 2018 Ghent University; imec; Fund for Scientific Research-Flanders (FWO-Flanders)
Support vector machine approach to fall recognition based on simplified expression of human skeleton action and fast detection of start key frame using torso angle [64] 2018  
Person re-identification using hybrid representation reinforced by metric learning [65] 2018  
Evolving head tracking routines with brain programming [66] 2018 Consejo Nacional de Ciencia y Tecnología; https://doi.org/10.13039/501100004963-seventh Framework Programme of the European Union through the Marie Curie International Research Staff Scheme, FP-PEOPLE-2013-IRSES, Project Analysis and Classification of Mental States of Vigilance with Evolutionary Computation; https://doi.org/10.13039/501100003089-centro de Investigación Científica y de Educación Superior de Ensenada, Baja California; TecNM Project 6474.18-P, “Navegación de robots móviles como un sistema adaptativo complejo.”
Natural language description of video streams using task-specific feature encoding [67] 2018 Basic Science Research Program through the National Research Foundation of Korea (NRF); Ministry of Education
Background subtraction using multiscale fully convolutional network [68] 2018 National Science Foundation of China
Face verification via learned representation on feature-rich video frames [69] 2017 MEITY, India, NVIDIA GPU grant, and Infosys CAI, IIIT-Delhi; IBM Ph.D. fellowship
Violent activity detection with transfer learning method [70] 2017  
Unsupervised sequential outlier detection with deep architectures [71] 2017  
High-level feature extraction for classification and person re-identification [72] 2017  
An ensemble of invariant features for person reidentification [73] 2017  
Facial expression recognition using salient features and convolutional neural network [74] 2017 Research Council of Norway as a part of the Multimodal Elderly Care Systems Project
Deep head pose: gaze-direction estimation in multimodal video [75] 2015  
Deep reconstruction models for image set classification [76] 2015 SIRF; University of Western Australia; ARC