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Reference changes · DOI

Information Processing in Agriculture 9(4), 485–496 (2022) https://doi.org/10.1016/j.inpa.2022.01.002

Published notice on a work cited in the Pith corpus. Exact quotes below. No model judges whether any citation was load-bearing.

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Correction Crossref 2 open · 2 total · 0 disputed
DOI
10.1016/j.inpa.2022.01.002
Notice DOI
10.1016/j.inpa.2023.08.004
Event date
2023-08-14
Machine twin
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01Notices on this DOI

02One-hop citing occurrences

Correction Open
LightTeaNet: A Weakly Supervised Lightweight CNN for Multi-Label Tea Leaf Disease Detection and Localization

ref [14] · 2608.14178 · notice #10779 · dispute

Raw extraction · bibliography line

Prasetyo, E., Purbaningtyas, R., Adityo, R.D., Suciati, N., Fatichah, C.: Combin- ing MobileNetV1 and depthwise separable convolution bottleneck with expansion for classifying the freshness of fish eyes. Information Processing in Agriculture 9(4), 485–496 (2022) https://doi.org/10.1016/j.inpa.2022.01.002
Correction Open
LightTeaNet: A Weakly Supervised Lightweight CNN for Multi-Label Tea Leaf Disease Detection and Localization

ref [14] · 2608.14178 · notice #10760 · dispute

Raw extraction · bibliography line

Prasetyo, E., Purbaningtyas, R., Adityo, R.D., Suciati, N., Fatichah, C.: Combin- ing MobileNetV1 and depthwise separable convolution bottleneck with expansion for classifying the freshness of fish eyes. Information Processing in Agriculture 9(4), 485–496 (2022) https://doi.org/10.1016/j.inpa.2022.01.002

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