Image Analytics: A consolidation of visual feature extraction methods. Issue 4 (2nd October 2021)
- Record Type:
- Journal Article
- Title:
- Image Analytics: A consolidation of visual feature extraction methods. Issue 4 (2nd October 2021)
- Main Title:
- Image Analytics: A consolidation of visual feature extraction methods
- Authors:
- Liu, Xiaohui
Liu, Fei
Li, Yijing
Shen, Huizhang
Lim, Eric T.K.
Tan, Chee-Wee - Abstract:
- Abstract : Revolutionary advances in machine and deep learning techniques within the field of computer field have dramatically expanded our opportunities to decipher the merits of digital imagery in the business world. Although extant literature on computer vision has yielded a myriad of approaches for extracting core attributes from images, the esotericism of the advocated techniques hinders scholars from delving into the role of visual rhetoric in driving business performance. Consequently, this tutorial aims to consolidate resources for extracting visual features via conventional machine and/or deep learning techniques. We describe resources and techniques based on three visual feature extraction methods, namely calculation-, recognition-, and simulation-based. Additionally, we offer practical examples to illustrate how image features can be accessed via open-sourced python packages such as OpenCV and TensorFlow.
- Is Part Of:
- Journal of management analytics. Volume 8:Issue 4(2021)
- Journal:
- Journal of management analytics
- Issue:
- Volume 8:Issue 4(2021)
- Issue Display:
- Volume 8, Issue 4 (2021)
- Year:
- 2021
- Volume:
- 8
- Issue:
- 4
- Issue Sort Value:
- 2021-0008-0004-0000
- Page Start:
- 569
- Page End:
- 597
- Publication Date:
- 2021-10-02
- Subjects:
- Image analytics -- attribute extraction -- computer vision -- deep learning -- Python
Management -- Mathematical models -- Periodicals
Management -- Periodicals
Management -- Mathematical models
Management
Periodicals
658.4033 - Journal URLs:
- http://www.tandfonline.com/toc/tjma20/1/1#.VQYnttqwopE ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/23270012.2021.1998801 ↗
- Languages:
- English
- ISSNs:
- 2327-0012
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 19938.xml