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Part 1: Document Description
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Citation |
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Title: |
Panda images dataset |
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Identification Number: |
doi:10.21979/N9/8CYVGF |
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Distributor: |
DR-NTU (Data) |
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Date of Distribution: |
2020-03-03 |
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Version: |
4 |
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Bibliographic Citation: |
Chen, Peng; Swarup, Pranjal; Matkowski, Wojciech Michal; Kong, Adams Wai Kin; Han, Su; Zhang, Zhihe; Rong, Hou, 2020, "Panda images dataset", https://doi.org/10.21979/N9/8CYVGF, DR-NTU (Data), V4 |
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Citation |
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Title: |
Panda images dataset |
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Identification Number: |
doi:10.21979/N9/8CYVGF |
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Authoring Entity: |
Chen, Peng (Chengdu Research Base of Giant Panda Breeding, Sichuan Key Laboratory of Conservation Biology for Endangered Wildlife, Sichuan Academy of Giant Panda) |
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Swarup, Pranjal (Nanyang Technological University) |
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Matkowski, Wojciech Michal (Nanyang Technological University) |
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Kong, Adams Wai Kin (Nanyang Technological University) |
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Han, Su (Sichuan Normal University) |
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Zhang, Zhihe (Chengdu Research Base of Giant Panda Breeding, Sichuan Key Laboratory of Conservation Biology for Endangered Wildlife, Sichuan Academy of Giant Panda) |
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Rong, Hou (Chengdu Research Base of Giant Panda Breeding, Sichuan Key Laboratory of Conservation Biology for Endangered Wildlife, Sichuan Academy of Giant Panda) |
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Software used in Production: |
Matlab |
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Software used in Production: |
Python |
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Grant Number: |
31300306 |
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Grant Number: |
2018JY0096 |
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Grant Number: |
2014‐02, 2014‐05 |
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Grant Number: |
CPB2018‐01, CPB2018‐02 |
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Grant Number: |
AD1417, CM1422 |
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Distributor: |
DR-NTU (Data) |
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Access Authority: |
Kong, Adams Wai Kin |
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Depositor: |
Swarup, Pranjal |
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Date of Deposit: |
2020-02-17 |
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Holdings Information: |
https://doi.org/10.21979/N9/8CYVGF |
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Study Scope |
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Keywords: |
Computer and Information Science, Medicine, Health and Life Sciences, Computer and Information Science, Medicine, Health and Life Sciences, Giant Panda, Image Recognition, Deep Learning |
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Abstract: |
The data used in the study titled "A Study on Giant Panda Recognition Based on Images of a Large Proportion of Captive Pandas". |
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Kind of Data: |
giant panda image data |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
Please communicate with Contact(s) for access |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Identification Number: |
10.1002/ece3.6152 |
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Bibliographic Citation: |
Chen, P., Swarup, P., Matkowski, W. M., Kong, A. W. K., Han, S., Zhang, Z., & Rong, H. (2020). A study on giant panda recognition based on images of a large proportion of captive pandas. Ecology and evolution, 10(7), 3561-3573. |
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Citation |
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Identification Number: |
10356/148620 |
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Bibliographic Citation: |
Chen, P., Swarup, P., Matkowski, W. M., Kong, A. W. K., Han, S., Zhang, Z. & Rong, H. (2020). A study on giant panda recognition based on images of a large proportion of captive pandas. Ecology and Evolution, 10(7), 3561-3573. |
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Label: |
annotations.7z |
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Text: |
Annotations of the raw images added separately. |
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Notes: |
application/x-7z-compressed |
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Label: |
images.7z.001 |
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Text: |
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip. |
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Notes: |
application/octet-stream |
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Label: |
images.7z.002 |
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Text: |
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip. |
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Notes: |
application/octet-stream |
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Label: |
images.7z.003 |
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Text: |
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip. |
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Notes: |
application/octet-stream |
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Label: |
images.7z.004 |
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Text: |
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip. |
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Notes: |
application/octet-stream |
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Label: |
images.7z.005 |
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Text: |
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip. |
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Notes: |
application/octet-stream |
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Label: |
images.7z.006 |
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Text: |
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip. |
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Notes: |
application/octet-stream |
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Label: |
images.7z.007 |
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Text: |
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip. |
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Notes: |
application/octet-stream |
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Label: |
images.7z.008 |
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Text: |
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip. |
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Notes: |
application/octet-stream |
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Label: |
images.7z.009 |
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Text: |
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip. |
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Notes: |
application/octet-stream |
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Label: |
images.7z.010 |
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Text: |
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip. |
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Notes: |
application/octet-stream |
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Label: |
images.7z.011 |
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Text: |
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip. |
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Notes: |
application/octet-stream |
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Label: |
images.7z.012 |
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Text: |
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip. |
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Notes: |
application/octet-stream |
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Label: |
images.7z.013 |
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Text: |
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip. |
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Notes: |
application/octet-stream |
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Label: |
panda_data_gen.zip |
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Text: |
Ground-truths generated from raw images and annotations using cropping, segmentation and alignment algorithms. |
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Notes: |
application/zip |
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Label: |
panda_data.zip |
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Text: |
Raw images in jpg format and annotations in csv formats. |
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Notes: |
application/zip |