Related references
Note: Only part of the references are listed.A novel automatic classification system based on hybrid unsupervised and supervised machine learning for electrospun nanofibers
Cosimo Ieracitano et al.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA (2021)
Multi-Column Atrous Convolutional Neural Network for Counting Metro Passengers
Jun Zhang et al.
SYMMETRY-BASEL (2020)
A two-step hybrid unsupervised model with attention mechanism for aspect extraction
Ganpat Singh Chauhan et al.
EXPERT SYSTEMS WITH APPLICATIONS (2020)
A survey of recent advances in CNN-based single image crowd counting and density estimation
Vishwanath A. Sindagi et al.
PATTERN RECOGNITION LETTERS (2018)
Crowded Scene Analysis: A Survey
Teng Li et al.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (2015)
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
Kaiming He et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2015)
A novel approach for crowd video monitoring of subway platforms
Xuernin Hu et al.
OPTIK (2013)
Pedestrian Detection: An Evaluation of the State of the Art
Piotr Dollar et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2012)
Shape-Based Human Detection and Segmentation via Hierarchical Part-Template Matching
Zhe Lin et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2010)
Detection and tracking of multiple, partially occluded humans by Bayesian combination of edgelet based part detectors
Bo Wu et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION (2007)
Estimation of number of people in crowded scenes using perspective transformation
SF Lin et al.
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS (2001)
Share Paper
