MammalClub: An Annotated Wild Mammal Dataset for Species Recognition, Individual Identification, and Behavior Recognition

Mammals play an important role in conserving species diversity and maintaining ecological balance, so research on mammal species composition, individual identification, and behavioral analysis is of great significance for optimizing the ecological environment. Due to their great capabilities for fea...

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Main Authors: Wenbo Lu, Yaqin Zhao, Jin Wang, Zhaoxiang Zheng, Liqi Feng, Jiaxi Tang
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Electronics
Subjects:
Online Access:https://www.mdpi.com/2079-9292/12/21/4506
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author Wenbo Lu
Yaqin Zhao
Jin Wang
Zhaoxiang Zheng
Liqi Feng
Jiaxi Tang
author_facet Wenbo Lu
Yaqin Zhao
Jin Wang
Zhaoxiang Zheng
Liqi Feng
Jiaxi Tang
author_sort Wenbo Lu
collection DOAJ
description Mammals play an important role in conserving species diversity and maintaining ecological balance, so research on mammal species composition, individual identification, and behavioral analysis is of great significance for optimizing the ecological environment. Due to their great capabilities for feature extraction, deep learning networks have gradually been applied to wildlife monitoring. However, training a network requires a large number of animal image samples. Although a few wildlife datasets contain many mammals, most mammal images in these datasets are not annotated. In particular, selecting mammalian images from vast and comprehensive datasets is still a time-consuming task. Therefore, there is currently a lack of specialized datasets of images of wild mammals. To address these limitations, this article created a mammal image dataset (named MammalClub), which contains three sub-datasets (i.e., a species recognition sub-dataset, an individual identification sub-dataset, and a behavior recognition sub-dataset). This study labeled the bounding boxes of the images used for species recognition and the coordinates of the mammals’ skeletal joints for behavior recognition. This study also captured images of each individual from different points of view for individual mammal identification. This study explored novel intelligent animal recognition models and compared and analyzed them with the mainstream models in order to test the dataset.
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spelling doaj.art-6b397e5b8a6a4950a5f3f08aa28674012023-11-10T15:01:40ZengMDPI AGElectronics2079-92922023-11-011221450610.3390/electronics12214506MammalClub: An Annotated Wild Mammal Dataset for Species Recognition, Individual Identification, and Behavior RecognitionWenbo Lu0Yaqin Zhao1Jin Wang2Zhaoxiang Zheng3Liqi Feng4Jiaxi Tang5College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, ChinaMammals play an important role in conserving species diversity and maintaining ecological balance, so research on mammal species composition, individual identification, and behavioral analysis is of great significance for optimizing the ecological environment. Due to their great capabilities for feature extraction, deep learning networks have gradually been applied to wildlife monitoring. However, training a network requires a large number of animal image samples. Although a few wildlife datasets contain many mammals, most mammal images in these datasets are not annotated. In particular, selecting mammalian images from vast and comprehensive datasets is still a time-consuming task. Therefore, there is currently a lack of specialized datasets of images of wild mammals. To address these limitations, this article created a mammal image dataset (named MammalClub), which contains three sub-datasets (i.e., a species recognition sub-dataset, an individual identification sub-dataset, and a behavior recognition sub-dataset). This study labeled the bounding boxes of the images used for species recognition and the coordinates of the mammals’ skeletal joints for behavior recognition. This study also captured images of each individual from different points of view for individual mammal identification. This study explored novel intelligent animal recognition models and compared and analyzed them with the mainstream models in order to test the dataset.https://www.mdpi.com/2079-9292/12/21/4506mammal datasetspecies recognitionindividual identificationbehavior recognition
spellingShingle Wenbo Lu
Yaqin Zhao
Jin Wang
Zhaoxiang Zheng
Liqi Feng
Jiaxi Tang
MammalClub: An Annotated Wild Mammal Dataset for Species Recognition, Individual Identification, and Behavior Recognition
Electronics
mammal dataset
species recognition
individual identification
behavior recognition
title MammalClub: An Annotated Wild Mammal Dataset for Species Recognition, Individual Identification, and Behavior Recognition
title_full MammalClub: An Annotated Wild Mammal Dataset for Species Recognition, Individual Identification, and Behavior Recognition
title_fullStr MammalClub: An Annotated Wild Mammal Dataset for Species Recognition, Individual Identification, and Behavior Recognition
title_full_unstemmed MammalClub: An Annotated Wild Mammal Dataset for Species Recognition, Individual Identification, and Behavior Recognition
title_short MammalClub: An Annotated Wild Mammal Dataset for Species Recognition, Individual Identification, and Behavior Recognition
title_sort mammalclub an annotated wild mammal dataset for species recognition individual identification and behavior recognition
topic mammal dataset
species recognition
individual identification
behavior recognition
url https://www.mdpi.com/2079-9292/12/21/4506
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