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Titlebook: Nature Inspired Optimization Techniques for Image Processing Applications; Jude Hemanth,Valentina Emilia Balas Book 2019 Springer Nature S

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書(shū)目名稱(chēng)Nature Inspired Optimization Techniques for Image Processing Applications
編輯Jude Hemanth,Valentina Emilia Balas
視頻videohttp://file.papertrans.cn/663/662009/662009.mp4
概述Covers most of the nature-inspired optimization algorithms in a single resource.Provides step-by-step algorithm coverage to facilitate implementation for budding researchers.Addresses specific applica
叢書(shū)名稱(chēng)Intelligent Systems Reference Library
圖書(shū)封面Titlebook: Nature Inspired Optimization Techniques for Image Processing Applications;  Jude Hemanth,Valentina Emilia Balas Book 2019 Springer Nature S
描述.This book provides a platform for exploring nature-inspired optimization techniques in the context of imaging applications. Optimization has become part and parcel of all computational vision applications, and since the amount of data used in these applications is vast, the need for optimization techniques has increased exponentially. These accuracy and complexity are a major area of concern when it comes to practical applications. However, these optimization techniques have not yet been fully explored in the context of imaging applications. By presenting interdisciplinary concepts, ranging from optimization to image processing, the book appeals to a broad readership, while also encouraging budding engineers to pursue and employ innovative nature-inspired techniques for image processing applications..
出版日期Book 2019
關(guān)鍵詞Nature Inspired Techniques; Optimization Algorithms; Image Processing; Computer Vision; Optimization; Nat
版次1
doihttps://doi.org/10.1007/978-3-319-96002-9
isbn_softcover978-3-030-07126-4
isbn_ebook978-3-319-96002-9Series ISSN 1868-4394 Series E-ISSN 1868-4408
issn_series 1868-4394
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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Plant Phenotyping Through Image Analysis Using Nature Inspired Optimization Techniques,occupies nearly 30?million hectares. The estimated wheat production in 2030 is about 700?million tones. Since we are in technical era, we can make use of those techniques to utilize for extracting the valuable information easily and accurately. Plant phenotyping is the process of the assessment of a
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Artificial Bee Colony Based Feature Selection for Automatic Skin Disease Identification of Mango Fr-day life, but there are diseases which affects the fruits and makes them non-edible or waste. These diseases in fruits also cause a huge problem in agricultural industries, worldwide. This research work presents the automatic skin disease identification system for mango fruit. Initially, the featur
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Analyzing the Effect of Optimization Strategies in Deep Convolutional Neural Network,ver, training DCNN is often complicated because of parameter initialization, overfitting and convergence problems. Hence this work has been targeted to overcome the challenges of training DCNN with an optimized model. This chapter describes a deep learning framework for image classification with cif
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