Crowd Flow Detection from Drones with Fully Convolutional Networks and Clustering-Reference-Cited by-同舟云学术

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Crowd Flow Detection from Drones with Fully Convolutional Networks and Clustering

Published:2022-07-18 Issue: Volume: Page:
ISSN:
Container-title:2022 International Joint Conference on Neural Networks (IJCNN)
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Author:

Castellano Giovanna¹,Mencar Corrado¹,Sette Gaetano¹,Troccoli Francesco Saverio¹,Vessio Gennaro¹

Affiliation:

1. University of Bari Aldo Moro,Department of Computer Science,Bari,Italy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9891857/9889787/09891954.pdf?arnumber=9891954

Reference33 articles.

1. VisDrone-DET2018: The Vision Meets Drone Object Detection in Image Challenge Results

2. A Cluster Separation Measure

3. Silhouettes: A graphical aid to the interpretation and validation of cluster analysis

4. Single-Image Crowd Counting via Multi-Column Convolutional Neural Network

5. CNN-based density estimation and crowd counting: A survey;gao;ArXiv Preprint,2020

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1. Learning Models in Crowd Analysis: A Review;Archives of Computational Methods in Engineering;2024-06-24

2. Improved Lightweight Head Detection Based on GhostNet-SSD;Neural Processing Letters;2024-03-29

3. Crowd counting in smart city via lightweight Ghost Attention Pyramid Network;Future Generation Computer Systems;2023-10

4. Density-based clustering with fully-convolutional networks for crowd flow detection from drones;Neurocomputing;2023-03

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