Deep Learning for Agricultural Visual Perception - Crop Pest and Disease Detection (1st ed. 2023)

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This monograph provides a detailed and systematic introduction to the application of deep learning technology in the intelligent monitoring of crop diseases and pests. Taking 24 types of crop pests, wheat aphids, and wheat diseases with complex backgrounds as examples, a large-scale crop pest and disease dataset was constructed to provide necessary data support for the deep learning module. Various schemes for identifying and detecting large-scale crop diseases and pests based on deep convolutional neural network technology have also been proposed. This book can be used as a reference for teachers and students majoring in agriculture, computer science, artificial intelligence, intelligent science and technology, and other related fields in higher education institutions. It can also be used as a reference book for researchers in fields such as image processing technology, intelligent manufacturing, and high-tech applications.

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Product Description

This monograph provides a detailed and systematic introduction to the application of deep learning technology in the intelligent monitoring of crop diseases and pests. Taking 24 types of crop pests, wheat aphids, and wheat diseases with complex backgrounds as examples, a large-scale crop pest and disease dataset was constructed to provide necessary data support for the deep learning module. Various schemes for identifying and detecting large-scale crop diseases and pests based on deep convolutional neural network technology have also been proposed. This book can be used as a reference for teachers and students majoring in agriculture, computer science, artificial intelligence, intelligent science and technology, and other related fields in higher education institutions. It can also be used as a reference book for researchers in fields such as image processing technology, intelligent manufacturing, and high-tech applications.

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Product Details

General

Imprint

Springer Verlag, Singapore

Country of origin

Singapore

Release date

September 2023

Availability

Expected to ship within 10 - 15 working days

First published

2023

Authors

, ,

Dimensions

235 x 155mm (L x W)

Pages

190

Edition

1st ed. 2023

ISBN-13

978-981-9949-72-4

Barcode

9789819949724

Categories

LSN

981-9949-72-6



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