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RGB-Based Deep Learning for Freeze Damage Detection in Strawberry: Comparing Scratch and Transfer Learning Approaches on Custom Data.

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Bibliographic Details
Title: RGB-Based Deep Learning for Freeze Damage Detection in Strawberry: Comparing Scratch and Transfer Learning Approaches on Custom Data.
Authors: Paul N; Department of Agricultural and Biosystems Engineering North Dakota State University Fargo North Dakota USA.; Genomics, Phenomics, and Bioinformatics program North Dakota State University Fargo North Dakota USA., Sunil GC; Department of Agricultural and Biosystems Engineering North Dakota State University Fargo North Dakota USA., Khan A; Department of Plant Sciences North Dakota State University Fargo North Dakota USA., Das S; Department of Agricultural and Biosystems Engineering North Dakota State University Fargo North Dakota USA., Hatterman-Valenti H; Department of Plant Sciences North Dakota State University Fargo North Dakota USA., Anderson JV; USDA-ARS-ETSARC Weed and Insect Biology Research Unit Fargo North Dakota USA., Kandel JS; USDA-ARS-ETSARC Weed and Insect Biology Research Unit Fargo North Dakota USA., Horvath D; USDA-ARS-ETSARC Weed and Insect Biology Research Unit Fargo North Dakota USA., Sun X; Department of Agricultural and Biosystems Engineering North Dakota State University Fargo North Dakota USA.
Source: Plant direct [Plant Direct] 2025 Dec 11; Vol. 9 (12), pp. e70124. Date of Electronic Publication: 2025 Dec 11 (Print Publication: 2025).
Publication Type: Journal Article
Journal Info: Publisher: John Wiley & Sons Ltd Country of Publication: England NLM ID: 101716131 Publication Model: eCollection Cited Medium: Internet ISSN: 2475-4455 (Electronic) Linking ISSN: 24754455 NLM ISO Abbreviation: Plant Direct Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2475-4455
DOI:10.1002/pld3.70124