A comparative study of deep learning and internet of things for precision agriculture
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Claims the paper makes
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
Data collected by drones on crop health, moisture levels, and soil conditions can be used to optimize crop yields and reduce waste.
“This data can then be used to optimize crop yields and reduce waste [97] .”
From Artificial intelligence, machine learning and deep learning in advanced robotics, a review (2023) · cites this paper as [97]
Drones equipped with AI and ML algorithms can be used to collect data on crop health, moisture levels, and soil conditions.
“Drones equipped with AI and ML algorithms can be used to collect data on crop health, moisture levels, and soil conditions.”
From Artificial intelligence, machine learning and deep learning in advanced robotics, a review (2023) · cites this paper as [97]
Cites
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
Alzubaidi, L., Zhang, J., Humaidi, A. J., Al-Dujaili, A., Duan, Y., Al-Shamma, O., Santamaría, J., Fadhel, M. A., Al-Amidie, M., & Farhan, L. (2021) · Journal of Big Data · doi:10.1186/s40537-021-00444-8 · Cited by 7,906 · see citing works
Sa, I., Popović, M., Khanna, R., Chen, Z., Lottes, P., Liebisch, F., Nieto, J., Stachniss, C., Walter, A., & Siegwart, R. (2018) · Remote Sensing · doi:10.3390/rs10091423 · Cited by 305 · see citing works
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Artificial intelligence, machine learning and deep learning in advanced robotics, a review
Soori, M., Arezoo, B., & Dastres, R. (2023) · Cognitive Robotics · doi:10.1016/j.cogr.2023.04.001 · Cited by 1,131 · see citing works
- Authors
- Saranya, T., Deisy, C., Sridevi, S., & Anbananthen, K. S. M.
- Affiliations
- Thiagarajar College of Engineering (IN)
- Multimedia University (MY)
- Corresponding author
- Saranya, T.
- Venue
- Engineering Applications of Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2023-06
- Volume
- 122
- Pages
- 106034
- ISSN
- 0952-1976 (ISSN-L)
- OpenAlex
- W4323306744
- Cited by
- 232
- References
- 2
- Citations by year
- 2026: 41 · 2025: 77 · 2024: 68 · 2023: 46
- FWCI
- 33.68
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Engineering Applications of Artificial Intelligence (publishedVersion)
- Siti Hasmah Digital Library-MMU Institutiona Repository (Multimedia University) (acceptedVersion)
- Funders
- Thiagarajar College of Engineering
- Topics
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Smart Agriculture and AI
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Keywords
- precision agriculture, deep learning in agriculture, Internet of Things in agriculture, pest detection, plant disease detection, crop yield prediction, weed detection, soil analysis, agricultural sensors, unmanned aerial vehicles, agricultural data, data augmentation, transfer learning, VGG16 fine-tuning
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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