Mango leaf disease detection and classification using image-based analysis : (Record no. 25365)

MARC details
000 -LEADER
fixed length control field 00570nam a2200157Ia 4500
003 - CONTROL NUMBER IDENTIFIER
control field NULRC
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250725162658.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250725s9999 xx 000 0 und d
040 ## - CATALOGING SOURCE
Transcribing agency lcc
050 ## - LIBRARY OF CONGRESS CALL NUMBER
Classification number UGT CCIT BSCS-ML .C49 2023
245 #0 - TITLE STATEMENT
Title Mango leaf disease detection and classification using image-based analysis :
Remainder of title a comparative study of efficientnetv2 models.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Manila :
Name of publisher, distributor, etc. National University,
Date of publication, distribution, etc. 2023
300 ## - PHYSICAL DESCRIPTION
Extent viii, 87 leaves ;
Dimensions 30 cm.
520 ## - SUMMARY, ETC.
Summary, etc. Mango is one of the most widely cultivated tropical fruits in the world.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Thesis
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection Home library Current library Shelving location Date acquired Source of acquisition Total checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
    Library of Congress Classification     Machine Learning LRC - Main National University - Manila Thesis 07/25/2025 Donation   UGT CCIT BSCS-ML .C49 2023 c.1 UGTHE000002604 07/25/2025 c.1 07/25/2025 Thesis