Pedestrian Detection Using Integrated Aggregate Channel Features and Multitask Cascaded Convolutional Neural-Network-Based Face Detectors

Pedestrian detection is a challenging task, mainly owing to the numerous appearances of human bodies. Modern detectors extract representative features via the deep neural network; however, they usually require a large training set and high-performance GPUs. For these cases, we propose a novel human...

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Bibliographic Details
Main Authors:	Barmpoutis, P. (Author), Stathaki, T. (Author), Yuan, J. (Author)
Format:	Article
Language:	English
Published:	MDPI 2022
Subjects:	Aggregate channel feature aggregate channel features Aggregates Combination of detector combination of detectors Convolution Convolutional networks Convolutional neural network Convolutional neural networks Deep neural networks Face detector Face recognition Feature extraction Multitask cascaded convolutional network multitask cascaded convolutional networks pedestrian detection Pedestrian detection Performance Program processors Statistical tests Test sets Training sets
Online Access:	View Fulltext in Publisher

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View Fulltext in Publisher

Pedestrian Detection Using Integrated Aggregate Channel Features and Multitask Cascaded Convolutional Neural-Network-Based Face Detectors

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