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ISSN No: 2349-2287 (P) | E-ISSN: 2349-2279 (O) | E-mail: editor@ijiiet.com

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International Research Journal of Infinite Innovations in Engineering and Technology (IJIIET)

| ISSN Approved Journal | Impact factor: 7.521 | Follows UGC CARE Journal Norms and Guidelines |

| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | Impact factor 7.521 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing) in all Major Database & Metadata, Citation Generator

Title : Natural Date Fruit Environment Classification Using CNN

Author : JANGILI RAVI KISHORE, VIJAYA BHASKAR MADGULA, DIGALA RAGHAVARAJU

Abstract :

Several applications in the pre- and post-harvest phases have their needs met by the creation of the date Fruit dataset. Visual yield estimate and mechanised harvesting are the two main uses. Each of the two subsets of the dataset is geared towards one of these two uses. There are a total of 8079 photos of over 350 date bunches taken from 29 different date palms in the first dataset. Each of the five varieties of dates—Naboot Saif, Khalas, Barhi, Meneifi, and Sullaj—is represented in the bunch. Six imaging sessions were used to obtain the photographs of the date bunches using a colour camera. All four phases of date maturity—immature, Khalal, Rutab, and Tamar—were addressed in the imaging sessions. To represent the difficulties in natural settings and date fruit orchards, the dataset is supplied with a high degree of diversity. Images may vary due to factors such as camera angle, scale, lighting, and the presence or absence of bags covering date bunches. Everything in th

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