RECPAD 2017 - THE 23th PORTUGUESE CONFERENCE ON PATTERN RECOGNITION
Welcome to RecPad 2017, the 23th edition of the Portuguese Conference on Pattern Recognition, sponsored by the APRP (Associação Portuguesa de Reconhecimento de Padrões - Portuguese Association for Pattern Recognition).
This year RecPad is held at the Portuguese Military Academy, Amadora (Lisbon) on October 27, 2017.
Authors are invited to submit two (2) pages of extended abstracts on topics such as artificial intelligence, image processing and machine vision. Papers covering theoretical and/or applied work on computer vision are invited. All papers will be reviewed "double blind", normally by two members of our Scientific Committee. The reviewers will judge submissions on originality, theoretical and/or experimental results, quality of evaluation, and presentation. The accepted papers will be compiled and distributed only in electronic format.
RecPad 2017 is a single-track meeting with only poster presentations and one keynote speaker.
RecPad 2017 is the Portuguese Conference on Pattern Recognition, sponsored by the APRP (Portuguese Association for Pattern Recognition). RecPad 2017 will take place at Portuguese Military Academy, Campus Amadora (Lisbon), Portugal, on October 27th, 2017. It is a one-day conference, with an invited talk and poster sessions.
RecPad 2017 promotes the collaboration between the Portuguese scientific community in the fields of Pattern Recognition, Image Analysis and Processing, Soft Computing, and related areas with example topics such as:
♦ Character recognition;
♦ Classification clustering ensembles and multi-classifiers;
♦ Data mining and big data;
♦ Feature extraction, discretization and selection;
♦ Fuzzy logic and fuzzy image processing;
♦ Gesture recognition;Hybrid methods;
♦ Image description and registration;
♦ Image enhancement, restoration and segmentation;
♦ Image understanding;Image fusion;
♦ Information theory;Intelligent systems;
♦ Machine vision;Neural network architectures;
♦ Object recognition;
♦ Pattern recognition applications;
♦ Sensors and sensor fusion;
♦ Soft computing techniques;
♦ Statistical methods;
♦ Syntactical methods.
The works should be submitted as extended abstracts for consideration by the Scientific Committee. The accepted papers will be compiled and distributed only in electronic format. The program of the conference is designed to allow travelling to Amadora (Lisbon) in the same day of the conference.
It is an ideal time for socializing and sharing experiences between young and senior researchers, showcasing their work and looking ahead to the future.
PDF version of the Call for Papers is available HERE.
We look forward to seeing you in Amadora (Lisbon).
♦ Submission of Papers:
September 4, 2017; ;
♦ Notification of Paper Acceptance:
September 25, 2017; ;
♦ Submission of Camera-ready Papers: October 8, 2017;
♦ Author Registration: October 8, 2017;
♦ Conference: October 27, 2017
Paul Scheunders, Vision Lab, University of Antwerp, Belgium.
Biography: Paul Scheunders received the Ph.D. degree in physics, with work in the field of statistical mechanics, from the University of Antwerp, Antwerp, Belgium, in 1990. In 1992, he became a research associate with the Vision Lab, Department of Physics, University of Antwerp, where he is currently a professor. His current research interest includes remote sensing and in particular hyperspectral image processing. He has published over 150 papers in international journals and proceedings in the field of image processing, pattern recognition and remote sensing.
Paul Scheunders is associate editor of the IEEE Transactions in Geoscience and Remote Sensing, and has served as program committee member in numerous international conferences. He is senior member of the IEEE Geoscience and Remote Sensing Society.
Keynote title: Machine Learning for remote sensing image analysis
Keynote abstract: In this talk, he will describe the state of the art on the development and application of machine learning methodologies in the remote sensing domain. He will also describe the specific remote sensing analysis problems that are typically handled by machine learning. On important type of sensor is the hyperspectral image sensor. Hyperspectral image sensors have been important tools for the characterization of materials based on their light reflectance mainly in remote sensing but in other domains as well. Hyperspectral images contain many spectral bands, each revealing the earth surface reflected light at a particular wavelength. These hyperspectral images require specific image processing and analysis methodologies. In this talk, an overview will be given of recent developments of machine learning in hyperspectral image analysis. Some of the strategies that are elaborated on are kernel methods, neural network methods, manifold learning methods, structured output methods, ensemble learning methods and sparse learning methods.
- Alexandre Bernardino (IST);
- Ana Fred (IST);
- Ana Aguiar (FEUP);
- Ana Maria Mendonça (FEUP);
- Ana Maria Tomé (UA);
- André Marçal (FCUP);
- Andrzej Wichert (IST);
- António Neves (UA);
- António Pinheiro (UBI);
- Armando Pinho (UA);
- Augusto Silva (UA);
- Aurélio Campilho (FEUP);
- Beatriz Sousa Santos (UA);
- Bernardete Ribeiro (UC),
- Catarina Silva (IPL);
- Fernando Monteiro (IPB);
- Hans du Buf (UAlg);
- Helder Araújo (UC);
- Hélder Oliveira (FCUP);
- Hugo Proença (UBI);
- Jaime Cardoso (FEUP);
- Jaime Santos (UC);
- Joao Barreto (UC);
- João Barroso (UTAD);
- João Cardoso (UC);
- João Rodrigues (UAlg);
- João Sanches (IST);
- João Tavares (FEUP);
- Joaquim Pinto da Costa (FCUP);
- Jorge Barbosa (FEUP);
- Jorge Batista (UC);
- Jorge S. Marques (IST);
- Jorge Santos (ISEP);
- Jorge Torres (Acad Militar);
- José Bioucas-Dias (IST);
- José Silva (Acad Militar);
- Luís A. Alexandre (UBI);
- Luís F. Teixeira (FEUP);
- Mário Figueiredo (IST);
- Miguel Coimbra (FCUP);
- Miguel Correia (IST);
- Noel Lopes (IPG);
- Nuno Martins (ISEC);
- Paulo Carvalho (UC);
- Paulo Oliveira (IST);
- Paulo Salgado (UTAD);
- Pedro Pina (IST);
- Ricardo Morla (FEUP);
- Rodrigo Ventura (IST);
- Samuel Silva (UA);
- Susana Vinga (IST);
- Thomas Gasche (Acad Militar);
- Verónica Vasconcelos (ISEC).
- Jose Silvestre Serra Silva, Chairman, (Military Academy);
- Jorge Paulo Alves Torres, (Military Academy);
- Pedro Nuno Mendonça dos Santos, (Military Academy);
- Thomas Peter Gasche, (Military Academy).
Local Technical Support
The papers should be submitted via EasyChair. The submission is done in four steps: set up an account with EasyChair, enter a paper title and abstract, and finally upload your paper. Please be sure to read the formatting instructions. Some common questions about submission can be send via the contact form. Submitted papers should be prepared according to the published specification for formatting and style.
Submit an article to RecPad 2017 here.
Formatting your paper
The authors are invited to submit papers in PDF format with not more than two (2) pages including results, figures and references, according to the formatting style. Papers which are overlength will not be reviewed.
Typesetting for review
Papers must be formatted for blind review and according to the following templates:
All accepted papers will be presented as posters.
The final version of the paper should add any information removed to anonymise the paper and remove any line numbering added for the review process. Please do take into account the comments from the reviewers when preparing the final version of your paper. Papers should be prepared according to the published specification for formatting and style. The length should not exceed two (2) pages.
♦ You will have a space for A0 portrait poster (85 x 120 cm maximum);
♦ Velcro pads or pins will be provided for affixing posters to the display boards.
♦ The company that will receive the Registration Form and the Payments is the “Wide Travel – Viagens e Turismo, Lda” with address “Av. Almirante Gago Coutinho nº 28 C; 1000-017 Lisboa” and NIF 508773911.
♦ The conference program: (not available at present);
♦ The conference proceeding: (not available at present).
Address: Avenida Conde Castro Guimarães, 2720-113 Amadora, Portugal
The city of Amadora is about 10/15 minutes by train from Lisbon. The Amadora train station is 10 minutes walk from the Portuguese Military Academy. You may check train time-table in:
Suggestion: Hotel Amadora Palace – This hotel is in centre of Amadora city, near train station, and a distance of 10 minutes walk from the Portuguese Military Academy.
How to contact the RECPAD2017 organization
Telephone (Academia Militar) 213 186 900 | Extension 412766
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