Neural Network-Based Vehicle and Pedestrian Detection for Video Analysis System

被引：0
作者：
Babayan, Pavel V. [1 ]
Ershov, Maksim D. [1 ]
Erokhin, Denis Y. [1 ]
机构：
[1] RSREU, Dept Automat & Informat Technol Control, Ryazan, Russia
来源：
2019 8TH MEDITERRANEAN CONFERENCE ON EMBEDDED COMPUTING (MECO) | 2019年
关键词：
video analysis; image processing; object detection; pattern recognition; neural networks; machine learning;
D O I：
10.1109/meco.2019.8760125
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In our research we compare various neural network architectures that are used for object detection and recognition. In this work vehicles and pedestrians are considered objects of interest. Modern artificial neural networks are able to detect and localize objects of known classes. This allows them to be used in various technical vision systems and video analysis systems. In this paper we compare three architectures (YOLO, Faster R-CNN, SSD) by the following criteria: processing speed, mAP, precision and recall.
引用
收藏
页码：310 / 314
页数：5
相关论文
共 50 条
  • [21] ViViD: View Prediction of Online Video Through Deep Neural Network-Based Analysis of Subjective Video Attributes
    Sarkar, Saikat
    Basu, Spandan
    Paul, Angshuman
    Mukherjee, Dipti Prasad
    IEEE TRANSACTIONS ON BROADCASTING, 2023, 69 (01) : 191 - 200
  • [22] Detection of lung injury with conventional and neural network-based analysis of continuous data
    Räsänen, J
    León, MA
    JOURNAL OF CLINICAL MONITORING AND COMPUTING, 1998, 14 (06) : 433 - 439
  • [23] A Neural Network-Based Method for Respiratory Sound Analysis and Lung Disease Detection
    Brunese, Luca
    Mercaldo, Francesco
    Reginelli, Alfonso
    Santone, Antonella
    APPLIED SCIENCES-BASEL, 2022, 12 (08):
  • [24] Deep Convolutional Neural Network-Based Autonomous Marine Vehicle Maneuver
    Qingyang Xu
    Yiqin Yang
    Chengjin Zhang
    Li Zhang
    International Journal of Fuzzy Systems, 2018, 20 : 687 - 699
  • [25] Convolutional neural network based object detection system for video surveillance application
    Bhimavarapu, John Philip
    Ramaraju, Sriharsha
    Nagajyothi, Dimmita
    Rao, Inumula Veeraraghava
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2023, 35 (03)
  • [26] Deep Convolutional Neural Network-Based Autonomous Marine Vehicle Maneuver
    Xu, Qingyang
    Yang, Yiqin
    Zhang, Chengjin
    Zhang, Li
    INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, 2018, 20 (02) : 687 - 699
  • [27] Formal Analysis and Redesign of a Neural Network-Based Aircraft Taxiing System with VERIFAI
    Fremont, Daniel J.
    Chiu, Johnathan
    Margineantu, Dragos D.
    Osipychev, Denis
    Seshia, Sanjit A.
    COMPUTER AIDED VERIFICATION (CAV 2020), PT I, 2020, 12224 : 122 - 134
  • [28] A neural network-based system for face detection in low quality web camera images
    Stathopoulou, Joanna-Ourania
    Tsihrintzis, George A.
    SIGMAP 2007: PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND MULTIMEDIA APPLICATIONS, 2007, : 53 - +
  • [29] Neural Network-Based Identification and Approximate Predictive Control of a Servo-Hydraulic Vehicle Suspension System
    Dahunsi, Olurotimi A.
    Pedro, Jimoh O.
    ENGINEERING LETTERS, 2010, 18 (04)
  • [30] Designing an Intelligent Rehabilitation Wheelchair Vehicle System Using Neural Network-based Torque Control Algorithm
    Kim, Taeyeun
    Bae, Sanghyun
    KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2017, 11 (12): : 5878 - 5904
12345