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Counting and Locating High-Density Objects Using Convolutional Neural
  Network

Counting and Locating High-Density Objects Using Convolutional Neural Network

Expert systems with applications (ESWA), 2021
8 February 2021
Mauro dos Santos de Arruda
L. Osco
Plabiany Rodrigo Acosta
D. Gonçalves
J. M. Junior
A. P. Ramos
E. Matsubara
Zhipeng Luo
Jonathan Li
J. Silva
W. Gonçalves
ArXiv (abs)PDFHTML

Papers citing "Counting and Locating High-Density Objects Using Convolutional Neural Network"

4 / 4 papers shown
Dense Center-Direction Regression for Object Counting and Localization
  with Point Supervision
Dense Center-Direction Regression for Object Counting and Localization with Point SupervisionPattern Recognition (Pattern Recogn.), 2024
Domen Tabernik
Jon Muhovič
D. Skočaj
3DPC
304
7
0
26 Aug 2024
BOLLWM: A real-world dataset for bollworm pest monitoring from cotton
  fields in India
BOLLWM: A real-world dataset for bollworm pest monitoring from cotton fields in India
J. White
Chandan Agrawal
Anmol Ojha
Apoorv Agnihotri
Makkunda Sharma
Jigar Doshi
271
1
0
03 Apr 2023
A Deep Learning Approach Based on Graphs to Detect Plantation Lines
A Deep Learning Approach Based on Graphs to Detect Plantation Lines
D. Gonçalves
Mauro dos Santos de Arruda
H. Pistori
V. Fernandes
A. P. Ramos
...
L. Osco
Hongjie He
Jonathan Li
J. M. Junior
W. Gonçalves
247
2
0
05 Feb 2021
YOLO9000: Better, Faster, Stronger
YOLO9000: Better, Faster, StrongerComputer Vision and Pattern Recognition (CVPR), 2016
Joseph Redmon
Ali Farhadi
VLMObjD
828
17,440
0
25 Dec 2016
1
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