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This includes the relevant datasets to: Khoroshevsky, F., Khoroshevsky, S., & Bar-Hillel, A. (2021). Parts-per-object count in agricultural images: Solving phenotyping problems via a single deep neural network. Remote Sens. 13(13), 2496. https://doi.org/10.3390/rs13132496 Datasets related to wheat and banana are not public since it belongs to the Israel Phenomics consortium. This research was funded by the Generic technological R&D program of the Israel innovation authority-the Phenomics consortium, and the Ministry of Science & Technology, Israel.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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