482 resources related to Information representation
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The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted full papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions,will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.
The CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020)
The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2020 will be the 17th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2020 meeting will continue this tradition of fostering cross-fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.
2020 IEEE 18th International Conference on Industrial Informatics (INDIN)
INDIN focuses on recent developments, deployments, technology trends, and research results in Industrial Informatics-related fields from both industry and academia
The International Conference on Information Fusion is the premier forum for interchange of the latest research in data and information fusion, and its impacts on our society. The conference brings together researchers and practitioners from academia and industry to report on the latest scientific and technical advances.
The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.
Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.
Speech analysis, synthesis, coding speech recognition, speaker recognition, language modeling, speech production and perception, speech enhancement. In audio, transducers, room acoustics, active sound control, human audition, analysis/synthesis/coding of music, and consumer audio. (8) (IEEE Guide for Authors) The scope for the proposed transactions includes SPEECH PROCESSING - Transmission and storage of Speech signals; speech coding; speech enhancement and noise reduction; ...
The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...
The IEEE Transactions on Automation Sciences and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. We welcome results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, ...
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693), 2003
In this paper, the application of D-S evidence theory in multi-feature, multi- neural network classifier pattern recognition has been researched. The key problem in determining the basic belief assignment (BBA) has been discussed in detail. A new method of determining the BBA based on neural network is presented in this paper. The result of traffic sign shape recognition experiment shows ...
IEEE Transactions on Circuits and Systems II: Express Briefs, 2006
We introduce a novel class of time encoding machines (TEMs) that exhibit multiplicative coupling, and, feedforward and feedback. We show that a machine with multiplicative coupling is I/O equivalent with an integrate-and-fire neuron with a variable threshold sequence. The same result holds for a TEM with feedforward while a machine with feedback is I/O equivalent with an asynchronous sigma/delta modulator ...
TENCON 2005 - 2005 IEEE Region 10 Conference, 2005
Multimedia data are illusory entities for the machines. Their contents include interpretable data as well as binary representations. Understanding and accessing the content-driven information for multimedia objects allow us to design an efficient multimedia querying and retrieval system. In this paper, we propose a framework to represent the multimedia information and object roles in order to generate automatic multimedia presentations. ...
IEEE Geoscience and Remote Sensing Letters, 2007
Hyperspectral images consist of large number of bands which require sophisticated analysis to extract. One approach to reduce computational cost, information representation, and accelerate knowledge discovery is to eliminate bands that do not add value to the classification and analysis method which is being applied. In particular, algorithms that perform band elimination should be designed to take advantage of the ...
2009 8th IEEE International Conference on Cognitive Informatics, 2009
Cognitive computing (CC) is an emerging paradigm of intelligent computing methodologies and systems that implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain [1, 3, 4, 5, 6, 12, 13, 15, 16, 18, 20, 22, 23]. CC is emerged and developed based on the transdisciplinary research in cognitive informatics and abstract intelligence. Cognitive informatics (CI) ...
The Autonomous City Explorer (ACE) Project--Mobile Robot Navigation in Highly Populated Urban Environments
A perspective shift from Fuzzy logic to Neutrosophic Logic - Swati Aggarwal
Solving Sparse Representation for Image Classification using Quantum D-Wave 2X Machine - IEEE Rebooting Computing 2017
IEEE Themes - Learning about human behavior from mobile phone data
ICASSP 2010 - Advances in Neural Engineering
Q&A with Dr. Atilla Elci: IEEE Big Data Podcast, Episode 10
Gender-Based Occupational Stereotypes: New Behaviors, Old Attitudes - Carolyn Matheus & Elizabeth Quinn - IEEE WIE Forum USA East 2017
A Roboticist, Ethicist and Novelist Walk Into a Bar: IEEE TechEthics Panel at SXSW
Adaptive Learning and Optimization for MI: From the Foundations to Complex Systems - Haibo He - WCCI 2016
A Conversation with…Richard Mallah: IEEE TechEthics
Information Technology: Careers for the information age
Self-Organization with Information Theoretic Learning
IEEE Future Directions: Green Information and Communications Technology: An Overview
Special Evening Panel Discussion: AI, Cognitive Information Processing, and Rebooting Computing - IEEE Rebooting Computing 2017
Data Modeling using Kernels and Information Theoretic Learning
Parallel Quantum Computing Emulation - Brian La Cour - ICRC 2018
Deep Learning and the Representation of Natural Data
From Bits to Atoms - Neil Gershenfeld: 2016 International Conference on Rebooting Computing
In this paper, the application of D-S evidence theory in multi-feature, multi- neural network classifier pattern recognition has been researched. The key problem in determining the basic belief assignment (BBA) has been discussed in detail. A new method of determining the BBA based on neural network is presented in this paper. The result of traffic sign shape recognition experiment shows that this new method can not only improve the total correct recognition percentage, but also reduce the fuzziness of decision-making and simplify the calculation.
We introduce a novel class of time encoding machines (TEMs) that exhibit multiplicative coupling, and, feedforward and feedback. We show that a machine with multiplicative coupling is I/O equivalent with an integrate-and-fire neuron with a variable threshold sequence. The same result holds for a TEM with feedforward while a machine with feedback is I/O equivalent with an asynchronous sigma/delta modulator with variable thresholds. For all TEMs, an input band-limited signal can be perfectly recovered from the zero crossings of the modulated signal and the threshold sequence. We present the optimal decoding algorithm and give conditions for perfect signal recovery
Multimedia data are illusory entities for the machines. Their contents include interpretable data as well as binary representations. Understanding and accessing the content-driven information for multimedia objects allow us to design an efficient multimedia querying and retrieval system. In this paper, we propose a framework to represent the multimedia information and object roles in order to generate automatic multimedia presentations. The proposed architecture attempts to represent the semantic information and the relations amongst the multimedia objects in a disclosure domain. Thus, the system is domain dependent. The represented data associates with the presentation mechanisms to create an integrated presentation generation system. A multi- layer design defines the various levels of abstraction for the proposed framework.
Hyperspectral images consist of large number of bands which require sophisticated analysis to extract. One approach to reduce computational cost, information representation, and accelerate knowledge discovery is to eliminate bands that do not add value to the classification and analysis method which is being applied. In particular, algorithms that perform band elimination should be designed to take advantage of the structure of the classification method used. This letter introduces an embedded-feature-selection (EFS) algorithm that is tailored to operate with support vector machines (SVMs) to perform band selection and classification simultaneously. We have successfully applied this algorithm to determine a reasonable subset of bands without any user- defined stopping criteria on some sample AVIRIS images; a problem occurs in benchmarking recursive-feature-elimination methods for the SVMs.
Cognitive computing (CC) is an emerging paradigm of intelligent computing methodologies and systems that implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain [1, 3, 4, 5, 6, 12, 13, 15, 16, 18, 20, 22, 23]. CC is emerged and developed based on the transdisciplinary research in cognitive informatics and abstract intelligence. Cognitive informatics (CI) is a transdisciplinary enquiry of computer science, information science, cognitive science, and intelligence science that investigates into the internal information processing mechanisms and processes of the brain and natural intelligence, as well as their engineering applications [1, 3, 6, 12, 13, 20, 22]. The theoretical framework of cognitive informatics  covers the Information-Matter-Energy (IME) model , the Layered Reference Model of the Brain (LRMB) , the Object- Attribute-Relation (OAR) model of information representation in the brain , the cognitive informatics model of the brain , Natural Intelligence (NI) , and neuroinformatics . Recent studies on LRMB in cognitive informatics reveal an entire set of cognitive functions of the brain and their cognitive process models, which explain the functional mechanisms and cognitive processes of the natural intelligence with 43 cognitive processes at seven layers known as the sensation, memory, perception, action, meta-cognitive, meta-inference, and higher cognitive layers from the bottom up .
XML is rapidly emerging as a standard for information storage, representation and exchange on the Web. How to rapidly search and query XML documents efficiently has received many attentions in resent research. However, current querying schemes of XML documents typically involve in both node content and tree structural information, which may limit efficiency when facing the application that the tree structural information is more complicated than the tree node itself. In this paper, we propose the node relationships joins algorithms that utilize available indexes mainly on tree structural information. The relationships join algorithms work perfectly especially for searching paths that are very long or whose lengths are unknown. Experimental results from our prototype system implementation highlight the correctness and efficiency of our solution
In this paper, a dynamic scene understanding concept is proposed and applied on multispectral image time series. Information mining enables the explorations and discovery of spatio temporal patterns localized in given spatio temporal windows. With this in mind, a hierarchical information representation is developed. It comprises different levels in which the data is modeled so that the relevant information is transmitted through the architecture, according to a query and to several assumptions made on the models employed. There are mainly four components: feature extraction, reduction of dimensionality, clustering and interactive exploration.
As fuzzy ontologies for fuzzy knowledge representation are increasingly constructed, how to store fuzzy ontologies is becoming a more pertinent issue. In this paper, we make use of the advantage of fuzzy relational database as an efficient solution to store fuzzy ontologies. Considering the characteristics of structure and individuals of fuzzy ontology we propose corresponding storage means, respectively. Moreover, the quality of storage of fuzzy ontology in fuzzy relational database is also discussed.
In this paper, based on spatial cognitive theories connected with the construction of natural language generation model for spatial information representation, we research on related spatial orientation results from the study field of modern Chinese, analyzed semantic mapping between spatial information represented by kinds of maps and spatial orientation information expressed by natural language, and bring spatial concept into the background of linguistics and GIS from a unique perspective. We determine the spatial information that should be represented in this kind of natural language, as well as set up intermediate semantic model which can be described by spatial point of point. This study is a contribution to summarize the macroscopic research achievements including spatial conception related to natural language, and generalize the microcosmic methods with respect to object-based spatial model and natural language generation. Implementation of a semantic framework mapped between spatial information and natural language is important from a methodological point of view because it guides us to build spatial knowledge base which formalize the semantics of natural language and specify spatial relation in a computational model which allows for similarity comparisons. This paper describes an experiment that investigates text generation result for bus route-finding.
The MATILDA multimedia authoring system has been developed to address issues related to authoring process and information management and representation. The paper presents our initial application of the structured graph visual formalism to the MATILDA data models. This has resulted in the introduction of a new group of automatically derivable links in the data models, and highlights some data model distinctions which we believe should be captured. We also discuss the possible use of the scalable editing and browsing operations that are part of the formalism.
his standard revises and enhances the VHDL language reference manual (LRM) by including a standard C language interface specification; specifications from previously separate, but related, standards IEEE Std 1164 -1993,1 IEEE Std 1076.2 -1996, and IEEE Std 1076.3-1997; and general language enhancements in the areas of design and verification of electronic systems.