Articles | Volume 18, issue 21
https://doi.org/10.5194/amt-18-6291-2025
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
In-line holographic droplet imaging: accelerated classification with convolutional neural networks and quantitative experimental validation
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- Final revised paper (published on 06 Nov 2025)
- Preprint (discussion started on 03 Apr 2025)
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
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RC1: 'Comment on egusphere-2025-612', Anonymous Referee #1, 09 May 2025
- AC1: 'Reply on RC1', Gholamhossein Bagheri, 31 Jul 2025
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RC2: 'Comment on egusphere-2025-612', Anonymous Referee #2, 23 May 2025
- AC2: 'Reply on RC2', Gholamhossein Bagheri, 31 Jul 2025
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RC3: 'Comment on egusphere-2025-612', Anonymous Referee #3, 10 Jun 2025
- AC3: 'Reply on RC3', Gholamhossein Bagheri, 31 Jul 2025
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Gholamhossein Bagheri on behalf of the Authors (31 Jul 2025)
Author's response
Author's tracked changes
Manuscript
ED: Publish subject to minor revisions (review by editor) (12 Aug 2025) by Luca Lelli
AR by Gholamhossein Bagheri on behalf of the Authors (21 Aug 2025)
Author's response
Author's tracked changes
Manuscript
ED: Publish as is (22 Aug 2025) by Luca Lelli
AR by Gholamhossein Bagheri on behalf of the Authors (29 Aug 2025)