2026-10-15T22:41:46Z https://data.mendeley.com/oai

oai:data.mendeley.com/z6dtfdpzz8.1 2022-12-28T20:29:09Z

Elhariri, esraa Strawberry-DS Mendeley Data - An annotated benchmark image dataset for training and validation of strawberry ripeness detection systems based on Machine learning (ML) and, Deep Learning (DL). - 247 Raw RGB digital images (.jpg) of strawberry fruits were taken in an orchard of the Central Laboratory for Agricultural Climate (CLAC), Agricultural Research Center, Cairo - Egypt. -The images have been captured from the fruit top view considering different view angles using Sony Xperia Z2 LTE-A D6503 smartphone 20.7 MP camera with a CMOS sensor system and resolution of 3840 x 2160 pixels (Mpix). The dataset images, which contain both fully-visible strawberry fruits and partially-visible strawberry fruits concealed by leaves or by other fruits, were manually annotated, using Roboflow Annotate annotation tool. The data formats of files in Strawberry-DS dataset are RGB digital images (.jpg) and their corresponding YOLO format (.txt) annotation files. Object Detection Machine Learning Fruit Developmental Stages Food Ripening Strawberry Deep Learning Crop Post Harvest Technology El-Bendary, Nashwa Elhariri, Esraa Dataset doi:10.17632/z6dtfdpzz8.1 oai:data.mendeley.com/z6dtfdpzz8.1 Creative Commons Attribution 4.0 International http://creativecommons.org/licenses/by/4.0 https://data.mendeley.com/datasets/z6dtfdpzz8 2022-12-28T20:29:09Z