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The two volume set LNCS 13258 and 13259 constitutes the proceedings of the International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2022, held in Puerto de la Cruz, Tenerife, Spain in May - June 2022. The total of 121 contributions was carefully reviewed and selected from 203 submissions. The papers are organized in two volumes, with the following topical sub-headings:Part I: Machine Learning in Neuroscience; Neuromotor and Cognitive Disorders; Affective Analysis; Health ApplicationsPart II: Affective Computing in Ambient Intelligence; Bioinspired Computing Approaches; Machine Learning in Computer Vision and Robot; Deep Learning; Artificial Intelligence Applications.

Video segmentation is the most fundamental process for appropriate index- ing and retrieval of video intervals. In general, video streams are composed 1 of shots delimited by physical shot boundaries. Substantial work has been done on how to detect such shot boundaries automatically (Arman et aI. , 1993) (Zhang et aI. , 1993) (Zhang et aI. , 1995) (Kobla et aI. , 1997). Through the inte- gration of technologies such as image processing, speech/character recognition and natural language understanding, keywords can be extracted and associated with these shots for indexing (Wactlar et aI. , 1996). A single shot, however, rarely carries enough amount of information to be meaningful by itself. Usu- ally, it is a semantically meaningful interval that most users are interested in re- trieving. Generally, such meaningful intervals span several consecutive shots. There hardly exists any efficient and reliable technique, either automatic or manual, to identify all semantically meaningful intervals within a video stream. Works by (Smith and Davenport, 1992) (Oomoto and Tanaka, 1993) (Weiss et aI. , 1995) (Hjelsvold et aI. , 1996) suggest manually defining all such inter- vals in the database in advance. However, even an hour long video may have an indefinite number of meaningful intervals. Moreover, video data is multi- interpretative. Therefore, given a query, what is a meaningful interval to an annotator may not be meaningful to the user who issues the query. In practice, manual indexing of meaningful intervals is labour intensive and inadequate.

Although there has been much progress in developing theories, models and systems in the areas of Natural Language Processing (NLP) and Vision Processing (VP), there has heretofore been little progress on integrating these two subareas of Artificial Intelligence (AI). This book contains a set of edited papers addressing theoretical issues and the grounding of representations in NLP and VP from philosophical and psychological points of view. The papers focus on site descriptions such as the reasoning work on space at Leeds, UK, the systems work of the ILS (Illinois, U.S.A.) and philosophical work on grounding at Torino, Italy, on Schank's earlier work on pragmatics and meaning incorporated into hypermedia teaching systems, Wilks' visions on metaphor, on experimental data for how people fuse language and vision and theories and computational models, mainly connectionist, for tackling Searle's Chinese Room Problem and Harnad's Symbol Grounding Problem. The Irish Room is introduced as a mechanism through which integration solves the Chinese Room. The U.S.A., China and the EU are well reflected, showing the fact that integration is a truly international issue. There is no doubt that all of this will be necessary for the SuperInformationHighways of the future.

This two-volume set constitutes the refereed proceedings of the 16th International Conference on Universal Access in Human-Computer Interaction, UAHCI 2022, held as part of the 24th International Conference, HCI International 2022, held as a virtual event, in June-July 2022. A total of 1271 papers and 275 posters included in the 39 HCII 2022 proceedings volumes. UAHCI 2022 includes a total of 73 papers; they focus on topics related to universal access methods, techniques and practices, studies on accessibility, design for all, usability, UX and technology acceptance, emotion and behavior recognition for universal access, accessible media, access to learning and education, as well universal access to virtual and intelligent assistive environments.

This book constitutes the proceedings of the 26th Annual Conference on Research in Computational Molecular Biology, RECOMB 2022, held in San Diego, CA, USA in May 2022. The 17 regular and 23 short papers presented were carefully reviewed and selected from 188 submissions. The papers report on original research in all areas of computational molecular biology and bioinformatics.

This book constitutes the refereed proceedings of the 10th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2022, held as part of Evo* 2022, in April 2022, co-located with the Evo* 2022 events, EvoCOP, EvoApplications, and EuroGP. The 20 full papers and 6 short papers presented in this book were carefully reviewed and selected from 66 submissions. They cover a wide range of topics and application areas, including generative approaches to music and visual art, deep learning, and architecture.

Digital image processing can refer to a wide variety of techniques, concepts, and applications of different types of processing for different purposes. This book provides examples of digital image processing applications and presents recent research on processing concepts and techniques. Chapters cover such topics as image processing in medical physics, binarization, video processing, and more.

Similarity-based learning methods have a great potential as an intuitive and ?exible toolbox for mining, visualization,and inspection of largedata sets. They combine simple and human-understandable principles, such as distance-based classi?cation, prototypes, or Hebbian learning, with a large variety of di?erent, problem-adapted design choices, such as a data-optimum topology, similarity measure, or learning mode. In medicine, biology, and medical bioinformatics, more and more data arise from clinical measurements such as EEG or fMRI studies for monitoring brain activity, mass spectrometry data for the detection of proteins, peptides and composites, or microarray pro?les for the analysis of gene expressions. Typically, data are high-dimensional, noisy, and very hard to inspect using classic (e. g. , symbolic or linear) methods. At the same time, new technologies ranging from the possibility of a very high resolution of spectra to high-throughput screening for microarray data are rapidly developing and carry thepromiseofane?cient,cheap,andautomaticgatheringoftonsofhigh-quality data with large information potential. Thus, there is a need for appropriate - chine learning methods which help to automatically extract and interpret the relevant parts of this information and which, eventually, help to enable und- standingofbiologicalsystems,reliablediagnosisoffaults,andtherapyofdiseases such as cancer based on this information. Moreover, these application scenarios pose fundamental and qualitatively new challenges to the learning systems - cause of the speci?cs of the data and learning tasks. Since these characteristics are particularly pronounced within the medical domain, but not limited to it and of principled interest, this research topic opens the way toward important new directions of algorithmic design and accompanying theory.

Mathematical Nonlinear Image Processing deals with a fast growing research area. The development of the subject springs from two factors: (1) the great expansion of nonlinear methods applied to problems in imaging and vision, and (2) the degree to which nonlinear approaches are both using and fostering new developments in diverse areas of mathematics. Mathematical Nonlinear Image Processing will be of interest to people working in the areas of applied mathematics as well as researchers in computer vision. Mathematical Nonlinear Image Processing is an edited volume of original research. It has also been published as a special issue of the Journal of Mathematical Imaging and Vision. (Volume 2, Issue 2/3).

A color time-varying image can be described as a three-dimensional vector (representing the colors in an appropriate color space) defined on a three-dimensional spatiotemporal space. In conventional analog television a one-dimensional signal suitable for transmission over a communication channel is obtained by sampling the scene in the vertical and tem­ poral directions and by frequency-multiplexing the luminance and chrominance informa­ tion. In digital processing and transmission systems, sampling is applied in the horizontal direction, too, on a signal which has been already scanned in the vertical and temporal directions or directly in three dimensions when using some solid-state sensor. As a conse­ quence, in recent years it has been considered quite natural to assess the potential advan­ tages arising from an entire multidimensional approach to the processing of video signals. As a simple but significant example, a composite color video signal, such as the conven­ tional PAL or NTSC signal, possesses a three-dimensional spectrum which, by using suitable three-dimensional filters, permits horizontal sampling at a rate which is less than that re­ quired for correctly sampling the equivalent one-dimensional signal. More recently it has been widely recognized that the improvement of the picture quality in current and advanced television systems requires well-chosen signal processing algorithms which are multidimen­ sional in nature within the demanding constraints of a real-time implementation.

A representation of objects by their parts is the dominant strategy for representing complex 3D objects in many disciplines. In computer vision and robotics, superquadrics are among the most widespread part models. Superquadrics are a family of parametric models that cover a wide variety of smoothly changing 3D symmetric shapes, which are controlled with a small number of parameters and which can be augmented with the addition of global and local deformations. The book covers, in depth, the geometric properties of superquadrics. The main contribution of the book is an original approach to the recovery and segmentation of superquadrics from range images. Several applications of superquadrics in computer vision and robotics are thoroughly discussed and, in particular, the use of superquadrics for range image registration is demonstrated. Audience: The book is intended for readers of all levels who are familiar with and interested in computer vision issues.

Images and video play a crucial role in visual information systems and multimedia. There is an extraordinary number of applications of such systems in entertainment, business, art, engineering, and science. Such applications often involved large image and video collections, and therefore, searching for images and video in large collections is becoming an important operation. Because of the size of such databases, efficiency is crucial. We strongly believe that image and video retrieval need an integrated approach from fields such as image processing, shape processing, perception, database indexing, visualization, and querying, etc. This book contains a selection of results that was presented at the Dagstuhl Seminar on Content-Based Image and Video Retrieval, in December 1999. The purpose of this seminar was to bring together people from the various fields, in order to promote information exchange and interaction among researchers who are interested in various aspects of accessing the content of image and video data. The book provides an overview of the state of the art in content-based image and video retrieval. The topics covered by the chapters are integrated system aspects, as well as techniques from image processing, computer vision, multimedia, databases, graphics, signal processing, and information theory. The book will be of interest to researchers and professionals in the fields of multimedia, visual information (database) systems, computer vision, and information retrieval.

Multimedia Mining: A Highway to Intelligent Multimedia Documents brings together experts in digital media content analysis, state-of-art data mining and knowledge discovery in multimedia database systems, knowledge engineers and domain experts from diverse applied disciplines.Multimedia documents are ubiquitous and often required, if not essential, in many applications today. This phenomenon has made multimedia documents widespread and extremely large. There are tools for managing and searching within these collections, but the need for tools to extract hidden useful knowledge embedded within multimedia objects is becoming pressing and central for many decision-making applications. The tools needed today are tools for discovering relationships between objects or segments within multimedia document components, such as classifying images based on their content, extracting patterns in sound, categorizing speech and music, and recognizing and tracking objects in video streams.

This two-volume set constitutes the refereed proceedings of the 5th European Conference on Computer Vision, ECCV'98, held in Freiburg, Germany, in June 1998.The 42 revised full papers and 70 revised posters presented were carefully selected from a total of 223 papers submitted. The papers are organized in sections on multiple-view geometry, stereo vision and calibration, geometry and invariances, structure from motion, colour and indexing, grouping and segmentation, tracking, condensation, matching and registration, image sequences and video, shape and shading, motion and flow, medical imaging, appearance and recognition, robotics and active vision, and motion segmentation.

Nel 1925, Economo e Koskinas pubblicarono l'atlante piu accurato e completo sulla citoarchitettonica della corteccia cerebrale umana mai realizzato. Una sintesi del contenuto dell'atlante venne in seguito resa disponibile in tedesco e tradotta in italiano, inglese e francese. Il valore scientifico di quest'opera e divenuto piu significativo negli ultimi vent'anni con l'avvento delle tecniche di neuroimaging funzionale, le quali consentono persino di rilevare specifici focolai di attivazione nella corteccia cerebrale umana durante l'esecuzione di compiti cognitivi. Questa riedizione in italiano e stata ampliata rispetto all'originale con l'aggiunta della mappa dei solchi e dei giri del cervello. Inoltre, e stata inclusa la tabella delle corrispondenze tra le aree individuate da Economo e Koskinas e quelle descritte da Brodmann. Il volume sara di grande interesse per tutti coloro che desiderano approfondire la relazione tra la struttura del cervello e le sue funzioni; rappresentera inoltre un utile strumento di lavoro per i professionisti che utilizzano le neuroimmagini nella loro pratica quotidiana, quali neurofisiologi, neuropsicologi, neuroradiologi, neurologi e neurochirurghi.