A Deep Dive into Precision Horticulture: Unravelling Olive Peacock Spot Intensity with Hybrid Deep Learning-Reference-Cited by-同舟云学术

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A Deep Dive into Precision Horticulture: Unravelling Olive Peacock Spot Intensity with Hybrid Deep Learning

Published:2024-05-24 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 5th International Conference for Emerging Technology (INCET)
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Author:

Banerjee Deepak¹,Sharma Neha¹,Chauhan Rahul²,Singh Mukesh³,Kumar Bura Vijay⁴

Affiliation:

1. Chitkara University Institute of Engineering and Technology, Chitkara University,Punjab,India

2. Graphic Era Hill University,Dehradun,Uttarakhand,India

3. Graphic Era Deemed to be University,Dehradun,Uttarakhand,India

4. School of Computer Science and Artificial Intelligence, SR University,Warangal,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10592862/10592849/10593619.pdf?arnumber=10593619

Reference14 articles.

1. Automatic Olive Peacock Spot Disease Recognition System Development by Using Single Shot Detector

2. Optimal Deep Learning Model for Olive Disease Diagnosis Based on an Adaptive Genetic Algorithm

3. Classification of olive leaf diseases using deep convolutional neural networks

4. An effective feature extraction method for olive peacock eye leaf disease classification

5. MobiRes-Net: A Hybrid Deep Learning Model for Detecting and Classifying Olive Leaf Diseases

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