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Pedestrian Detection with Deep Convolutional Neural Network
[chapter]
2015
Lecture Notes in Computer Science
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In this paper, we propose to cascade simple Aggregated Channel Features (ACF) and rich Deep Convolutional Neural Network (DCNN) features for efficient and effective pedestrian detection in complex scenes ...
The problem of pedestrian detection in image and video frames has been extensively investigated in the past decade. ...
And in [22] authors further cooperated with Convolutional Neural Network, and proposed a joint deep learning framework that jointly consider four key components in pedestrian detection: feature extraction ...
doi:10.1007/978-3-319-16628-5_26
fatcat:jxqdw4peuvbkbcqi3mrk7jopgq
Pedestrian detection based on deep convolutional neural network with ensemble inference network
2015
2015 IEEE Intelligent Vehicles Symposium (IV)
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In this paper, we propose the methods based on Convolutional Neural Networks (CNN) that achieves high accuracy in various fields. ...
Pedestrian detection is an active research topic for driving assistance systems. ...
Pedestrian detection based on Deep Convolutional Neural Networks (CNN) achieved the high detection accuracy in the pedestrian detection benchmark [6] . ...
doi:10.1109/ivs.2015.7225690
dblp:conf/ivs/FukuiYYFM15
fatcat:zzbqcj5yqnhw3ehhg25aazyeou
Deep Convolutional Neural Network for Pedestrian Detection with Multi-Levels Features Fusion
2018
MATEC Web of Conferences
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Pedestrian detection aims to localize and recognize every pedestrian instance in an image with a bounding box. ...
The contribution of this paper is integrated low-level features and high-level features into a Faster RCNN-based pedestrian detection framework, which efficiently increase the capacity of the feature. ...
Girshick et al. first introduced convolutional neural network framework for general object detection by Regions with CNN (RCNN). ...
doi:10.1051/matecconf/201823201061
fatcat:twe2v3tupzgn5nzcf5a3wfzm5m
Distant Pedestrian Detection in the Wild using Single Shot Detector with Deep Convolutional Generative Adversarial Networks
2019
2019 International Joint Conference on Neural Networks (IJCNN)
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In this work, we examine the feasibility of applying Deep Convolutional Generative Adversarial Networks (DCGANs) with Single Shot Detector (SSD) as data-processing technique to handle with the challenge ...
of pedestrian detection in the wild. ...
PROPOSED DCGAN-SSD ARCHITECTURE FOR PEDESTRIAN DETECTION
A. ...
doi:10.1109/ijcnn.2019.8851859
dblp:conf/ijcnn/DinakaranEZBJE19
fatcat:ackc2t7c5fdjrkh4kbdqyk6dka
Pedestrian classification on transfer learning based deep convolutional neural network for partial occlusion handling
2023
International Journal of Power Electronics and Drive Systems (IJPEDS)
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The development of deep convolutional neural networks has significantly improved the autonomous driver assistance system for pedestrian classification. ...
<span lang="EN-US">The investigation of a deep neural network for pedestrian classification using transfer learning methods is proposed in this study. ...
neural network with 22 layers and tiny convolutional filters with 1×1 and 5×5 convolutions. ...
doi:10.11591/ijece.v13i3.pp2812-2826
fatcat:rffdy7j3pjcspevuohffswtak4
Automated Pedestrian Recognition Based on Deep Convolutional Neural Networks
2019
International Journal of Machine Learning and Computing
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However, deep Convolutional Neural Networks (i.e. CNNs) achieved promising results in various recognition tasks. ...
Index Terms-Neural network, machine learning, pedestrian recognition, deep learning. ...
Section II presents Deep Convolutional Neural Network and the proposed deep learning architecture. ...
doi:10.18178/ijmlc.2019.9.5.855
fatcat:jgfls27xbfeu5dvsifv6jehuxa
Deep Convolutional Neural Networks for pedestrian detection
2016
Signal processing. Image communication
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In this paper, we propose a pedestrian detection system based on deep learning, adapting a general-purpose convolutional network to the task at hand. ...
In the last few years, deep learning and in particular convolutional neural networks emerged as the state of the art in terms of accuracy for a number of computer vision tasks such as image classification ...
Optimizing deep convolutional networks for pedestrian detection The use of Convolutional Neural Networks in the context of pedestrian detection is recent, and the potential of such ap- proach is still ...
doi:10.1016/j.image.2016.05.007
fatcat:puvk6ytkxvebtporop4cpetx3a
Pedestrian Detection based on Faster R-CNN
2019
International Journal of Performability Engineering
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In this paper, the Faster R-CNN target detection model is combined with the convolutional neural networks VGG16 and ResNet101 respectively, and the deep convolutional neural network is used to extract ...
Pedestrian detection has a wide range of applications, such as intelligent assisted driving, intelligent monitoring, pedestrian analysis, and intelligent robotics. ...
Compared to traditional methods, Faster R-CNN differs in that it replaces regional proposals with deep convolutional neural networks. ...
doi:10.23940/ijpe.19.07.p5.17921801
fatcat:o6fzvcxxprcqnfi4hpkqnpkvmm
Scale-Adaptive KCF Mixed with Deep Feature for Pedestrian Tracking
2021
Electronics
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By introducing deep features extracted by a newly designed neural network and by introducing the YOLOv3 (you only look once version 3) object detection algorithm, which was also improved for more accurate ...
Pedestrian tracking methods include neural network-based methods and traditional template matching-based methods, such as the SiamRPN (Siamese region proposal network), the DASiamRPN (distractor-aware ...
When the pedestrian is occluded and the KCF target is lost, the convolutional neural network used for extracting the deep features of pedestrians is used to compare the last deep feature before the occlusion ...
doi:10.3390/electronics10050536
fatcat:mt4eamk4vnfqdetfu3i5btxbeq
Guest Editors' Introduction: Special issue on deep learning with applications to visual representation and analysis
2016
Signal processing. Image communication
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A deep learning based pedestrian detection system is developed in the paper "Deep Convolutional Neural Networks for Pedestrian Detection" by Denis Tomè, Federico Monti, Luca Baroffio, Luca Bondi, Marco ...
convolutional neural networks with respect to facial landmark misalignment. ...
doi:10.1016/j.image.2016.09.003
fatcat:ufz6tbhkwzhapjysq564cm5e54
An Investigation of a Convolution Neural Network Architecture for Detecting Distracted Pedestrians
2020
International Journal of Advanced Computer Science and Applications
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This work tested three different architectures of convolutional neural networks. These architectures are Basic, Deep, and AlexNet. ...
Thus, this research aims to investigate how to use the convolutional neural networks for building an algorithm that significantly improves the accuracy of detecting distracted pedestrians based on gathered ...
[18] Deep convolutional neural networks demonstrated amazing performance in pedestrians and attribute detection and were selected as the approach for this research.
III. ...
doi:10.14569/ijacsa.2020.0110279
fatcat:2ngbgdax7zhg5ptn2ntr5zlchi
Pedestrian Detection with Semantic Regions of Interest
2017
Sensors
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First, we generate a pedestrian heat map from the input image with a full convolutional neural network trained on the Caltech Pedestrian Dataset. ...
We test our approach on the Caltech Pedestrian Detection Benchmark. With the help of our semantic regions of interest, the effects of the detectors have varying degrees of improvement. ...
Figure 2 . 2 Key idea of our approach for pedestrian detection. (a) is the ordinary image, transferred to the heat map (b) with the deep neural network. ...
doi:10.3390/s17112699
pmid:29165372
pmcid:PMC5713501
fatcat:m7dclsn4dbhx3fsb3jawclgz2u
Pedestrian Detection Based on Fast R-CNN and Batch Normalization
[chapter]
2017
Lecture Notes in Computer Science
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With the development of deep learning method, pedestrian detection has achieved great success. ...
Sermanet et al. (2013) proposed a two layers convolutional model which adopts convolutional sparse coding to pre-train convolutional neural network for pedestrian detection. Chen et al. ...
So deep neural networks trained with batch normalization can converge faster and generalize better. ...
doi:10.1007/978-3-319-63309-1_65
fatcat:a7axvzw25faf5g465a5ygl57vi
Application of Multi-Feature Fusion Based on Deep Learning in Pedestrian Re-Recognition Method
2022
Mobile Information Systems
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To increase the consistency of the data, the multi-level spatial convolution structure was merged with the entire image in this paper. ...
The application approach for pedestrian re-recognition based on deep learning for numerous features is proposed in this paper. ...
Training of Convolution Neural Network
Deep Learning Propagation Algorithm. e forward neural network structure of deep learning is divided into deep learning input and deep learning output. e progress ...
doi:10.1155/2022/5292134
fatcat:dei6okfyhjhinlvd2feqv5h56i
Towards Pedestrian Detection Using RetinaNet in ECCV 2018 Wider Pedestrian Detection Challenge
[article]
2019
arXiv
pre-print
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Wider pedestrian detection challenge aims at finding improve solutions for pedestrian detection problem. In this paper, We propose a pedestrian detection system based on RetinaNet. ...
Recent deep learning based methods have shown state-of-the-art performance in computer vision tasks such as image classification, object detection, and segmentation. ...
Due to the success of deep neural networks in classification tasks, many researchers focus on detecting pedestrian and object using convolutional neural networks. Tome et al. ...
arXiv:1902.01031v1
fatcat:oirbxnjaerb7tpckanr3caeokq
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