AI-Algorithms for Classification & Prediction of Tomato Plant Disease
| AUTHOR | R, Harikrishnan; Wagle, Shivali Amit |
| PUBLISHER | LAP Lambert Academic Publishing (02/21/2023) |
| PRODUCT TYPE | Paperback (Paperback) |
Description
Three novel deep convolutional neural networks models are discussed for the classification of tomato plant leaves. The performance of the augmented and original datasets is compared using state-of-the-art models such as AlexNet, GoogLeNet, VGG16, MobileNetV2, SqueezeNet, ResNet-18, ResNet-50, and ResNet-101 with transfer learning. The tomato plant diseases namely early blight, late blight, bacterial spot, leaf mold, mosaic virus, target spot, Septoria leaf spot, yellow leaf curl virus and leaf miner are discussed in this book. Temperature and relative humidity play a major role in susceptible environmental conditions for plants disease. Forecasting of these parameters is done using models viz. ARIMA, Prophet, Long Short-Term Memory, and Bilinear Long Short-Term Memory with Bayesian optimization.
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Product Format
Product Details
ISBN-13:
9786206145936
ISBN-10:
620614593X
Binding:
Paperback or Softback (Trade Paperback (Us))
Content Language:
English
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Page Count:
164
Carton Quantity:
44
Product Dimensions:
6.00 x 0.38 x 9.00 inches
Weight:
0.55 pound(s)
Country of Origin:
US
Subject Information
BISAC Categories
Computers | General
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publisher marketing
Three novel deep convolutional neural networks models are discussed for the classification of tomato plant leaves. The performance of the augmented and original datasets is compared using state-of-the-art models such as AlexNet, GoogLeNet, VGG16, MobileNetV2, SqueezeNet, ResNet-18, ResNet-50, and ResNet-101 with transfer learning. The tomato plant diseases namely early blight, late blight, bacterial spot, leaf mold, mosaic virus, target spot, Septoria leaf spot, yellow leaf curl virus and leaf miner are discussed in this book. Temperature and relative humidity play a major role in susceptible environmental conditions for plants disease. Forecasting of these parameters is done using models viz. ARIMA, Prophet, Long Short-Term Memory, and Bilinear Long Short-Term Memory with Bayesian optimization.
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$102.12