CNN-LSTM Learning Approach for Classification of Foliar Disease of Apple-Reference-Cited by-同舟云学术

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CNN-LSTM Learning Approach for Classification of Foliar Disease of Apple

Published:2023-01-23 Issue: Volume: Page:
ISSN:
Container-title:2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)
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Author:

Haruna Ahmed Abba¹,Badi Ibrahim Ahmed²,Muhammad L. J.³,Abuobieda Albaraa¹,Altamimi Abdulaziz¹

Affiliation:

1. University of Hafr Al Batin,College of Computer Science and Engineering,Department of Computer Science,Hafr Al Batin,Saudi Arabia

2. Libyan Academy,Mechanical Engineering Department,Misurata,Libya

3. Federal University of Kashere,Computer Science Department,Gombe,Nigeria

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10084917/10084937/10085039.pdf?arnumber=10085039

Reference30 articles.

1. Bidirectional Convolutional LSTM for the Detection of Violence in Videos;hanson,2018

2. Deep Learning Models for Classification and Localization of COVID-19 Abnormalities on Chest Radiographs

3. The Plant Pathology Challenge 2020 data set to classify foliar disease of apples

4. COVID-19 Diagnosis from Chest CT Scans: A Weakly Supervised CNN-LSTM Approach

5. A Composite Approach For Site Optimization Of Fire Stations

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