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CrowdDCNN: Deep convolution neural network for real-time crowd counting on IoT edge

  • Published:2023-11 Issue: Volume:126 Page:107089
  • ISSN:0952-1976
  • Container-title:Engineering Applications of Artificial Intelligence
  • language:en
  • Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Chavan Rugved,kanamarlapudi Aravind,Rani Geeta,Thakkar PriyamORCID,Dhaka Vijaypal SinghORCID

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference37 articles.

1. Yolov4: Optimal speed and accuracy of object detection;Bochkovskiy,2020

2. Crowdnet: A deep convolutional network for dense crowd counting;Boominathan,2016

3. Privacy preserving crowd monitoring: Counting people without people models or tracking;Chan,2008

4. Comprehensive review on intelligent traffic management system in india;Chavan,2022

5. Iot-enabled sustainable solution for smart shopping experience;Chavan,2023

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Resource-constrained edge-based deep learning for real-time person-identification using foot-pad;Engineering Applications of Artificial Intelligence;2024-12

2. Cross-modal misalignment-robust feature fusion for crowd counting;Engineering Applications of Artificial Intelligence;2024-10

3. Cerberus;Proceedings of the 7th International Workshop on Edge Systems, Analytics and Networking;2024-04-22

4. Lightweight Res-Connection Multi-Branch Network for Highly Accurate Crowd Counting and Localization;Computers, Materials & Continua;2024
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