Aphid Cluster Recognition and Detection in the Wild Using Deep Learning Models (doi:10.7910/DVN/JBAEFB)

View:

Part 1: Document Description
Part 2: Study Description
Part 5: Other Study-Related Materials
Entire Codebook

Document Description

Citation

Title:

Aphid Cluster Recognition and Detection in the Wild Using Deep Learning Models

Identification Number:

doi:10.7910/DVN/JBAEFB

Distributor:

Harvard Dataverse

Date of Distribution:

2023-02-17

Version:

1

Bibliographic Citation:

Wang, Richard, 2023, "Aphid Cluster Recognition and Detection in the Wild Using Deep Learning Models", https://doi.org/10.7910/DVN/JBAEFB, Harvard Dataverse, V1

Study Description

Citation

Title:

Aphid Cluster Recognition and Detection in the Wild Using Deep Learning Models

Identification Number:

doi:10.7910/DVN/JBAEFB

Authoring Entity:

Wang, Richard

Distributor:

Harvard Dataverse

Access Authority:

Wang, Richard

Depositor:

Wang, Richard

Date of Deposit:

2023-02-17

Holdings Information:

https://doi.org/10.7910/DVN/JBAEFB

Study Scope

Keywords:

Agricultural Sciences, Computer and Information Science

Abstract:

@inproceedings{zhang2023new, title={A New Dataset and Comparative Study for Aphid Cluster Detection}, author={Zhang, Tianxiao and Li, Kaidong and Chen, Xiangyu and Zhong, Cuncong and Luo, Bo and Teran, Ivan Grijalva and McCornack, Brian and Flippo, Daniel and Sharda, Ajay and Wang, Guanghui}, booktitle={2nd AAAI Workshop on AI for Agriculture and Food Systems}, year={2023} }

Methodology and Processing

Sources Statement

Data Access

Other Study Description Materials

Other Study-Related Materials

Label:

aphid2022.z01

Notes:

application/octet-stream

Other Study-Related Materials

Label:

aphid2022.z02

Notes:

application/octet-stream

Other Study-Related Materials

Label:

aphid2022.zip

Notes:

application/zip