id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
easat-11220	Nurahman, Nurahman; Minarni, Minarni; Aziz, Abdul; Winarti, Lili; Mashami, Eddy; Prabowo, Dwi Wahyu	Palm fruit ripeness classification using BorneoNet for improved accuracy in precision agriculture	2025	13	.pdf	application/pdf	6887	370	46	[22] utilized Raman spectroscopy to identify molecular characteristics such as protein, lipid, carotene, and guanine/cytosine, and employed an ANN model, achieving 97.9 percent accuracy in classifying oil palm fruit ripeness. Application of BorneoNet for palm fruit ripeness classification: The introduction of BorneoNet provides a novel and efficient approach to ripeness classification, specifically designed to match the characteristics of the palm fruit dataset while maintaining computational efficiency.	cache/easat-11220.pdf	txt/easat-11220.txt