@inproceedings{65ea2ec9de9d46cc837a81b446a4454c,
title = "Density Map Estimation for Crowded Chicken",
abstract = "Intensive breeding is the trend of the breeding industry. In order to make it more convenient to manage and reduce labor costs, sometimes we need to estimate the number of individuals in the poultry farm and discriminate the density distribution to help scientific management. At the same time, crowd density estimation is a developing research direction in deep learning. There are both similarities and differences between crowd counting task and chicken counting task. Aimed at the characteristics of poultry farm images, this paper presents a solution to density estimation and counting of poultry individuals in poultry farm by deep network method. We designed an end to end model and transform the problem into a pixel-level classification problem to get the density map.",
keywords = "Density estimation, Flock counting, Pixel level classification",
author = "Dong Cheng and Tianze Rong and Guitao Cao",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 10th International Conference on Image and Graphics, ICIG 2019 ; Conference date: 23-08-2019 Through 25-08-2019",
year = "2019",
doi = "10.1007/978-3-030-34113-8\_36",
language = "英语",
isbn = "9783030341121",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "432--441",
editor = "Yao Zhao and Chunyu Lin and Nick Barnes and Baoquan Chen and R{\"u}diger Westermann and Xiangwei Kong",
booktitle = "Image and Graphics - 10th International Conference, ICIG 2019, Proceedings, Part 3",
address = "德国",
}