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"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."

"This book covers two essential PDE-based image processing fields: image denoising and image inpainting. It describes the state-of-the-art PDE-based image restoration and interpolation (inpainting) techniques, focusing on the latest advances in PDE-based image processing and analysis, and explores novel techniques involving diffusion-based models and variational schemes. The PDE and variational schemes clearly outperform the conventional approaches in these areas, and can successfully remove image noise and reconstruct missing or highly degraded regions, while preserving the essential features and avoiding unintended effects. The book addresses researchers and graduate students, but is also well suited for professionals in both the mathematics and electrical engineering domains, as it provides rigorous mathematical investigations of the image processing models described, as well as mathematical treatments for the numerical approximation schemes of these differential models. "

"This book covers all main aspects of guidance information processing technologies for airborne optical imaging seekers, including theoretical models; image pre-processing; automatic target detection, recognition and tracking; and embedded real-time processing systems. The book is divided into three major sections: firstly, a theoretical model for optical-seeker information processing is introduced; then information processing methods are presented, including target modeling, online image pre-processing, typical surface fixed-target detection and recognition, and moving-target detection and recognition; lastly, embedded real-time processing systems are introduced, including new system architectures, image processing ASIC/SoC design, embedded real-time operating systems, system implementation aspects, and system testing and evaluation technologies. The book offers a unique and valuable resource, helping readers understand both fundamental and advanced information processing technologies employed in airborne optical imaging seekers. "

"This book features high-quality research papers presented at the International Conference on Advanced Computing and Intelligent Engineering (ICACIE 2017). It includes sections describing technical advances in the fields of advanced computing and intelligent engineering, which are based on the presented articles. Intended for postgraduate students and researchers working in the discipline of computer science and engineering, the proceedings also appeal to researchers in the domain of electronics as it covers hardware technologies and future communication technologies."

"In this new edition of the Handbook of Signal Processing Systems, many of the chapters from the previous editions have been updated, and several new chapters have been added. The new contributions include chapters on signal processing methods for light field displays, throughput analysis of dataflow graphs, modeling for reconfigurable signal processing systems, fast Fourier transform architectures, deep neural networks, programmable architectures for histogram of oriented gradients processing, high dynamic range video coding, system-on-chip architectures for data analytics, analysis of finite word-length effects in fixed-point systems, and models of architecture. There are more than 700 tables and illustrations; in this edition over 300 are in color. This new edition of the handbook is organized in three parts. Part I motivates representative applications that drive and apply state-of-the art methods for design and implementation of signal processing systems; Part II discusses architectures for implementing these applications; and Part III focuses on compilers, as well as models of computation and their associated design tools and methodologies. "

"The book provides copyright protection approaches for videos using watermarking. The various watermarking techniques using various transforms such as discrete cosine transform (DCT), discrete wavelet transform (DWT) and singular value decomposition (SVD) for videos are presented. The book also provides video watermarking approach using compressive sensing (CS) theory. The presented watermarking techniques are designed and implemented using color digital videos. The performance of the presented techniques is evaluated using Peak Signal to Noise Ratio (PSNR) and Normalized Correlation (NC)."

"This volume presents up-to-date material on the state of the art in evolutionary and deterministic methods for design, optimization and control with applications to industrial and societal problems from Europe, Asia, and America.EUROGEN 2015 was the 11th of a series of International Conferences devoted to bringing together specialists from universities, research institutions and industries developing or applying evolutionary and deterministic methods in design optimization, with emphasis on solving industrial and societal problems.The conference was organised around a number of parallel symposia, regular sessions, and keynote lectures focused on surrogate-based optimization in aerodynamic design, adjoint methods for steady & unsteady optimization, multi-disciplinary design optimization, holistic optimization in marine design, game strategies combined with evolutionary computation, optimization under uncertainty, topology optimization, optimal planning, shape optimization, and production scheduling."

"ABSTRAKDalam beberapa tahun terakhir, Deep Learning DL telah menarik banyak perhatian dalam penelitian pemelajaran mesin. Metode ini telah berhasil dipakai untuk berbagai aplikasi pada pemrosesan suatu, robotika, pengenalan fonetik, pencarian informasi dan bahkan analisa molekul. Meskipun DL telah berhasil sukses untuk diterapkan dalam berbagai bidang aplikasi, training yang diperlukan pada metode ini tidaklah mudah. Sejumlah cara telah diusulkan untuk membuat proses training DL menjadi lebih optimal, beberapa diantanya dengan menambahkan proses pre-training, memutuskan beberapa jaringan dalam lapisan, ataupun mengganti fungsi aktivasi dan metode gradien standar yang dipergunakan. Disertasi ini menggunakan pendekatan lain dalam optimasi DL, yaitu memakai algoritme metaheuristik. Secara umum disertasi ini dibagi dalam dua bagian besar. Bagian pertama adalah studi awal penelitian yang difokuskan pada beberapa eksperimen yang berkaitan dengan algoritme metaheuristik dan aplikasi DL dalam klasifikasi citra. Bagian kedua dari disertasi berkaitan dengan penerapan algoritme metaheuristik dalam DL. Hasil pada bagian ini misalnya untuk optimasi metode Convolutional Neural Nework CNN menggunakan dataset CIFAR10, diperoleh untuk Top-1 error pada validasi adalah 99,05 . Hasil ini lebih baik dari nilai akurasi CNN asli sebesar 88,21 , fine-tuning CNN menggunakan Harmony Search yang diusulkan G. Rosa dkk sebesar 78,28 , dan bahkan State of the art saat ini sebesar 96,53 dengan Fractional Max-Pooling.

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ABSTRACTIn recent years, deep Learning DL has drawn many attention in machine learning research. This method has been successfully used in various applications, such as sound process, robotics, phonetic identification, information retrieval, and even molecule analysis. Although DL has been successful to be applied in many fields, it is difficult to train in this method. Various attempts and methods has been proposed to make the DL training process become more optimum, some of them are by adding pre training process, drop out some networks in the layer, or by replacing activation function and standard gradient method being used. This dissertation takes another way to optimize a DL, i.e. using metaheuristic algorithms. Overall, this dissertation will be divided into two main parts. The first part is a preliminary study of research, focusing on several experiments which were related to the metaheuristic algorithm and DL application in image classification. The second part of this dissertation is related to application of metaheuristic algorithm in DL. The results in this part, for example, the optimization of CNN method using CIFAR10 dataset for Top 1 error in validation is 99.05 . This result is higher than the accuracy level from original CNN 88,21 , fine tuning CNN using Harmony Search suggested by G. Rossa et.al 78.28 , and even ldquo State of the art rdquo right now using Fractional Max Pooling 96.53 "

"The book includes selected high-quality research papers presented at the Third International Congress on Information and Communication Technology held at Brunel University, London on February 27–28, 2018. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of Things (IOT), and e-mining. Written by experts and researchers working on ICT, the book is suitable for new researchers involved in advanced studies."