Some lattice computing approaches towards computational intelligence, image processing and analysis

• Grant number: 18/13657-1
• Support Opportunities: Regular Research Grants
• Start date: September 01, 2018
• End date: August 31, 2020
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Peter Sussner
• Grantee: Peter Sussner
• Host Institution: Instituto de Matemática, Estatística e Computação Científica (IMECC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• City of the host institution: Campinas

Abstract

The technical term "lattice computing" was recently coined to refer to an evolving collection of tools and mathematical models for processing lattice ordered data such as numbers, intervals, possibility and probability distributions, (fuzzy) sets, extensions of fuzzy sets as well as other types of information granules. Note that many classes of information granules such as the classes of the extended integers, the extended reals, intervals, as well as classes of fuzzy sets and several of their extensions represent complete lattices that have played important roles in mathematical morphology and fuzzy set theory since many years. Since the 1990's, some researchers including myself are transferring operators, ideas, and concepts of lattice algebra into the area of computational intelligence. The goal of this research project is to develop new lattice computing approaches towards computational intelligence as well as image processing and analysis, in particular approaches towards L-fuzzy mathematical morphology and L-fuzzy systems, where L denotes an arbitrary complete lattice or semilattice. (AU)

Scientific publications

(10)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

SUSSNER, PETER; CARO CONTRERAS, DAVID ERNESTO. Generalized morphological components based on interval descriptors and n-ary aggregation functions. INFORMATION SCIENCES, v. 583, p. 14-32, JAN 2022. (18/13657-1, 20/09838-0)

SUSSNER, PETER; CAMPIOTTI, ISRAEL. Extreme learning machine for a new hybrid morphological/linear perceptron. NEURAL NETWORKS, v. 123, p. 288-298, MAR 2020. (18/13657-1, 17/10224-4)

WASQUES, VINICIUS F.; ESMI, ESTEVAO; BARROS, LAECIO C.; SUSSNER, PETER. The generalized fuzzy derivative is interactive. INFORMATION SCIENCES, v. 519, p. 93-109, MAY 2020. (18/13657-1, 16/26040-7)

EDUARDO SANCHEZ, DANIEL; WASQUES, VINICIUS FRANCISCO; ESMI, ESTEVAO; DE BARROS, LAECIO CARVALHO; SUSSNER, PETER. Fuzzy Initial Value Problems for Fuzzy Hypocycloid Curves. 2019 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, FUZZ-IEEE, v. N/A, p. 5-pg., 2019-01-01. (18/10946-2, 18/13657-1, 16/26040-7)

SUSSNER, PETER; CARAZAS, LISBETH CORBACHO; NOVAK, V; MARIK, V; STEPNICKA, M; NAVARA, M; HURTIK, P. An Approach Towards Image Edge Detection Based on Interval-Valued Fuzzy Mathematical Morphology and Admissible Orders. PROCEEDINGS OF THE 11TH CONFERENCE OF THE EUROPEAN SOCIETY FOR FUZZY LOGIC AND TECHNOLOGY (EUSFLAT 2019), v. 1, p. 8-pg., 2019-01-01. (18/13657-1)

WASQUES, VINICIUS F.; ESMI, ESTEVAO; BARROS, LAECIO C.; SUSSNER, PETER. Numerical Solution for Fuzzy Initial Value Problems via Interactive Arithmetic: Application to Chemical Reactions. INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, v. 13, n. 1, p. 1517-1529, 2020. (16/26040-7, 18/13657-1)

WASQUES, VINICIUS F.; ESMI, ESTEVAO; BARROS, LAECIO C.; SUSSNER, P.; NOVAK, V; MARIK, V; STEPNICKA, M; NAVARA, M; HURTIK, P. Numerical Solution for Lotka-Volterra Model of Oscillating Chemical Reactions with Interactive Fuzzy Initial Conditions. PROCEEDINGS OF THE 11TH CONFERENCE OF THE EUROPEAN SOCIETY FOR FUZZY LOGIC AND TECHNOLOGY (EUSFLAT 2019), v. 1, p. 6-pg., 2019-01-01. (18/13657-1, 16/26040-7)

SUSSNER, PETER; CAMPIOTT, ISRAEL; QUISPE TORRES, MANUEL ALEJANDRO; IEEE. Hybrid Gray-Scale and Fuzzy Morphological/Linear Perceptrons Trained By Extreme Learning Machine. 2020 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), v. N/A, p. 8-pg., 2020-01-01. (18/13657-1, 17/10224-4)

SUSSNER, PETER; ESMI, ESTEVAO; JARDIM, LUIS GUSTAVO; KEARFOTT, RB; BATYRSHIN, I; REFORMAT, M; CEBERIO, M; KREINOVICH, V. A Subsethod Interval Associative Memory with Competitive Learning. FUZZY TECHNIQUES: THEORY AND APPLICATIONS, v. 1000, p. 12-pg., 2019-01-01. (18/13657-1, 16/26040-7)

SUSSNER, PETER; ESMI, ESTEVAO; FLORINDO, JOAO. A New Algorithm for Designing Θ-Fuzzy Associative Memories Based on Subsethood Measures. 2019 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, FUZZ-IEEE, v. N/A, p. 6-pg., 2019-01-01. (18/13657-1, 16/16060-0, 16/26040-7)