Cascade CNN Framework for Low Resolution Image Classification (Record no. 14248)
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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 | 20210210122912.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 210210b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | AIKTC-KRRC |
| Transcribing agency | AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 13255 |
| Author | Kannojia, Suresh Prasad |
| 245 ## - TITLE STATEMENT | |
| Title | Cascade CNN Framework for Low Resolution Image Classification |
| 250 ## - EDITION STATEMENT | |
| Volume, Issue number | Vol 6 (1), Jan-Apr |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | New Delhi |
| Name of publisher, distributor, etc. | STM Journals |
| Year | 2019 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Pagination | 39-43p. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | : Low resolution images contain less visual information, so classifications of these images are difficult. For overcoming this problem, cascade CNN framework for low resolution image classification is proposed. In this framework, super resolution CNN (SRCNN) enlarges low resolution image into super resolution image. The convolutional features of these super resolution images are fused with low resolution convolutional features which are extracted by low resolution CNN (LRCNN) feature extractor. A deep neural network classifier is trained on these fused CNN features. This classifier classifies low resolution images using learned fused features. Proposed cascade framework has been evaluated on different benchmark image dataset MNIST, CIFAR10 and achieves competitive accuracy results. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| 9 (RLIN) | 4622 |
| Topical term or geographic name entry element | Computer Engineering |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 13256 |
| Co-Author | Jaiswal, Gaurav |
| 773 0# - HOST ITEM ENTRY | |
| Title | Journal of artificial intelligence research and advances (JoAIRA) |
| Place, publisher, and date of publication | Noida STM Journals |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| URL | http://computers.stmjournals.com/index.php?journal=JoAIRA&page=article&op=view&path%5B%5D=1910 |
| 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 |
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| Dewey Decimal Classification | School of Engineering & Technology | School of Engineering & Technology | Archieval Section | 10/02/2021 | 2021-2021469 | 10/02/2021 | 10/02/2021 | Articles Abstract Database |