Categorization of leaf ailments using deep learning techniques: a review (Record no. 17493)
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| 000 -LEADER | |
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| fixed length control field | a |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220912100257.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 220912b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | AIKTC-KRRC |
| Transcribing agency | AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 17849 |
| Author | Golla, Mahalaxmi |
| 245 ## - TITLE STATEMENT | |
| Title | Categorization of leaf ailments using deep learning techniques: a review |
| 250 ## - EDITION STATEMENT | |
| Volume, Issue number | Vol.14(1), Feb |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Hyderabad |
| Name of publisher, distributor, etc. | IUP Publications |
| Year | 2022 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Pagination | 50-65p. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Computerized image processing techniques are extremely useful in agriculture. The technology can help detect plant diseases and improve cultivation quality. The study examines the advantages and disadvantages of previous research on the subject. To find the most effective image processing methods for diagnosing plant diseases, cutting-edge techniques are examined. To find plant pathogens, many computerized image processing methods are used. This review compares the results and many different approaches to develop algorithms such as Support Vector Machines (SVM) and Deep Learning Neural Networks (DLNN), which are important in the detection and classification of leaf diseases. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| 9 (RLIN) | 4619 |
| Topical term or geographic name entry element | EXTC Engineering |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 17848 |
| Co-Author | Tirupal, T. |
| 773 0# - HOST ITEM ENTRY | |
| Place, publisher, and date of publication | Hyderabad IUP Publications |
| International Standard Serial Number | 0975-5551 |
| Title | IUP Journal of telecommunications |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| URL | https://iupindia.in/0222/Telecommunications/Categorization_of_Leaf.asp |
| Link text | Click here |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Articles Abstract Database |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total Checkouts | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | School of Engineering & Technology | School of Engineering & Technology | Archieval Section | 12/09/2022 | 2022-1561 | 12/09/2022 | 12/09/2022 | Articles Abstract Database |