W01 –Correspondence Problem In Computer Vision and Pattern Recognition (CPPR18)
Overview
The recent years have witnessed the significant advancement of techniques for automatic correspondence among visual data. Although visual correspondence has been well studied in multi-view geometry, its generalized forms, and the potential connections with other relevant tasks, are still not fully investigated. Meanwhile, the big data and deep learning paradigm, which has achieved major success in perceptual tasks, has still not been well capitalized for visual correspondence. In this workshop, we attempt to assemble recent advances in the correspondence problem, in an effort for connecting the local and global structures with the modern learning and data processing paradigms.
Organizers
Junchi Yan Shanghai Jiao Tong University
Shuhan Shen Institute of Automation, Chinese Academy of Sciences
Changsheng Li University of Electronic Science and Technology of China
Schedule
Venue: Room 301A
Time: 20th August 2018, 14:05 - 16:00 PM
SUBSLOT
SPEAKER
TITLE
CHAIR
14:05 - 14:10
Opening remarks
Shuhan Shen
14:10 - 14:40
Yihong Wu
Invited Talk 1: Image based
camera localization towards challenging problems
Shuhan Shen
14:45 - 15:15
Xiaowei Zhou
Invited Talk 2: Finding consistent feature correspondences
across multiple images
Junchi Yan
15:20 - 16:00
Xu-Cheng Yin
Invited Talk 3: Tacking based
text detection and recognition from scene and web videos
Changsheng Li
Additional Information
Workshop Website:http://vision.ia.ac.cn/CCPRWorkshop2018/index.html
W02 –Computer Vision for Analysis of Underwater Imagery (CVAUI 2018)
Overview
The analysis of underwater imagery imposes a series of unique challenges, which need to be tackled by the computer vision community in collaboration with biologists and ocean scientists. We invite submissions from all areas of computer vision and image analysis relevant for, or applied to, underwater image analysis.
Organizers
Alexandra Branzan Albu University of Victoria, BC, Canada
Maia Hoeberechts Ocean Networks Canada, Victoria, BC, Canada
Schedule
Venue: Room 301B
Time: 20th August 2018, 09:00 AM - 17:00 PM
SUBSLOT
SPEAKER/TITLE
09:00 - 09:30
Welcome from Workshop Organizers (Alexandra
Branzan Albu & Maia Hoeberechts)
“Big data” challenges in underwater imagery
analysis (Maia Hoeberechts)
09:30 - 10:30
Invited Talk 1:Kim
Juniper (Ocean Networks Canada, University of Victoria, Victoria, Canada)
10:30 - 11:00
Coffee Break
11:00 - 12:30
Oral Presentations 1 (4 papers)
Single Image Plankton 3D Reconstruction from
Extended Depth of Field Shadowgraph
Claudius Zelenka1 and Reinhard Koch1
1Department
of Computer Science, Kiel University, Germany
Deep Active Learning for In Situ Plankton
Classification
Erik Bochinski1, Ghassen Bacha1,
Volker Eiselein1, Tim J. W. Walles2, Jens C.Nejstgaard2,
and Thomas Sikora1
1 Communication System Group, Technische Universität Berlin
2 Leibnitz-Institute of Freshwater Ecology and Inland Fisheries
Tracking Sponge Size and Behaviour with Fixed
Underwater Observatories
Torben Möller1, Ingunn Nilssen2,
and Tim Wilhelm Nattkemper1
1 Biodata Mining Group, Bielefeld University, Bielefeld 33615, Germany
2 Equinor, Research and Technology, Trondheim 7005 Norway
Underwater-GAN: Underwater Image Restoration via
Conditional Generative Adversarial Network
Xiaoli Yu1, Yanyun Qu1, and
Ming Hong1
1School
of Information Science and Engineering, Xiamen University, Xiamen, China
12:30 - 14:00
Lunch
14:00 - 15:30
Oral Presentations 2 (4
papers)
Strategies for
Tackling the Class Imbalance Problem in Marine Image Classification
Daniel Langenkämper1,
Robin van Kevelaer1, and Tim W Nattkemper1
1Biodata Mining Group, Faculty of Technology,
Bielefeld University, 33615 Bielefeld, Germany
Marine Snow Removal Using a Fully Convolutional 3D
Neural Network Combined with an Adaptive Median Filter
Michał Koziarski1 and Bogusław Cyganek1
1Department
of Electronics, AGH University of Science and Technology, Kraków, Poland
An Online Platform for Underwater Image Quality
Evaluation
Chau Yi Li1, Riccardo Mazzon1,
Andrea Cavallaro1
1Centre
for Intelligent Sensing, Queen Mary University of London
Enhancement of low-lighting underwater images
using Dark Channel Prior and Fast Guided Filters
Tunai Porto Marques1, Alexandra
Branzan Albu1 and Maia Hoeberechts2
1 Department of Electrical & Computer Engineering, University of
Victoria, Victoria, Canada
2 Ocean Networks
Canada, University of Victoria, Victoria, Canada
15:30 - 16:00
Coffee Break
16:00 - 17:00
Invited Talk 2:Bob Fisher (School of
Informatics, University of Edinburgh, Edinburgh, Scotland, UK)
Additional Information
Workshop Website:http://cvaui2018.oceannetworks.ca
W03+W04- The Second International Workshop on Deep Learning for Pattern Recognition (DLPR2018)
Overview
Deep Learning, which can be treated as the most significant breakthrough in the past 10 years in the field of pattern recognition and machine learning, has greatly affected the methodology of related fields like computer vision and achieved terrific progress in both academy and industry. It can be seen as a resolution to change the whole pattern recognition system. It achieved an end-to-end pattern recognition, merging the previous steps of pre-processing, feature extraction, classifier design and post-processing. It is expected that the development of deep learning theories and applications would further influence the field of pattern recognition. The major goal of this workshop is to provide a platform for researchers or graduate students around the world to report or exchange their progresses on deep learning for pattern recognition.
Organizers
Xiang Bai Huazhong University Science and Technology
Yi Fang New York University Abu Dhabi and New York University
Yangqing Jia Facebook
Meina Kan Institute of Computing Technology, Chinese Academy of Sciences
Shiguang Shan Institute of Computing Technology, Chinese Academy of Sciences
Chunhua Shen University of Adelaide
Jingdong Wang Microsoft Research Asia
Gui-Song Xia Wuhan University
Shuicheng Yan National University of Singapore
Zhaoxiang Zhang Institute of Automation, Chinese Academy of Sciences
Kamal Nasrollahi Aalborg University, Denmark
Gang Hua Microsoft Research, USA
Thomas B. Moeslund Aalborg University, Denmark
Qiang Ji Rensselaer Polytechnic Institute, USA
Schedule
Venue: Room 306B
Time: 20thAugust 2018, 13:30 - 17:00 PM
SUBSLOT |
SPEAKER |
TITLE |
CHAIR |
13:30 - 13:40 |
Welcome and Opening |
Zhaoxiang Zhang |
|
13:40 - 14:20 |
Edwin Hancock (University of York, UK) |
Machine Learning with Quantum Walks |
Guisong Xia |
14:20 - 15:00 |
Xilin Chen(Institute of Computing Technology of the Chinese Academy of Sciences) |
TBD |
Kamal Nasrollahi |
15:00 - 15:10 |
Michał Koziarski, Bogdan Kwolek and Bogusław Cyganek |
Convolutional Neural Network-Based Classification of Histopathological Images Affected by Data Imbalance |
Kamal Nasrollahi |
15:10 - 15:20 |
Fu Hao, Ming Yue, Jiang Yibo and Fan Chunxiao |
Effective SVD-based Deep Network Compression for Automatic Speech Recognition |
|
15:20 - 15:30 |
Kang Liao, Chunyu Lin, Yao Zhao and Moncef Gabbouj |
DRGAN: Automatic Radial Distortion Rectification Using Conditional GAN in Real-Time |
|
15:30 - 15:40 |
Fadi Dornaika, Fawzi Khattar, Jorge Reta, Ignacio Arganda-Carreras and Yassine Ruichek |
Image-based Driver Drowsiness Detection |
|
15:40 - 16:00 |
Coffee Break |
||
16:00 - 16:10 |
Chao Li and Yue Ming |
Three-Stream Convolution networks after background subtraction for action recognition |
Meina Kan |
16:10 - 16:20 |
Cong Luo and Xue Gao |
Scene Text Detection with A SSD and Encoder-Decoder Network Based Method |
|
16:20 - 16:30 |
Arindam Das, Thomas Boulay and Senthil Yogamani |
Evaluation of Group Convolution in Lightweight Deep Networks for Object Classification |
|
16:30 - 16:40 |
Javier Hernandez-Ortega, Julian Fierrez, Ester Gonzalez-Sosa and Aythami Morales |
Continuous Presentation Attack Detection in Face Biometrics based on Heart Rate |
|
16:40 – 17:00 |
Closing |
Workshop Website: https://dlpr2018.github.io/home/index.html
Workshop Website:https://ffer.aau.dk/
W05 - 7th IAPR International Workshop on Computational Forensics
Overview
With the advent of high-end technology, fraudulent efforts are on rise in many areas of our daily life, may it be fake paper documents, forgery in the digital domain or copyright infringement. In solving the related criminal cases use of pattern recognition (PR) principles is also gaining an important place because of their ability in successfully assisting the forensic experts to solve many of such cases.
The 7th IAPR International Workshop on Computational Forensics (IWCF) will aim at addressing the theoretical and practical issues related to this field, i.e. role of PR techniques for analysing problems in forensics. Effort is to bring the people together who are working on these issues in different areas including document and speech processing, music analysis, digital security, forensic sciences, etc.
Organizers
Jean-Marc Ogier University of La Rochelle, France
Chang-Tsun Li Charles Sturt University, Australia
Nicolas Sidère University of La Rochelle, France
Schedule
Venue: Room 302B
Time: 20thAugust 2018, 09:00 – 12:00 AM
SUBSLOT |
SPEAKER/TITLE |
09:00 – 10:00 |
Chang-Tsun Li Applications Of Multimedia Forensics In Law Enforcement |
10:00 – 10:15 |
A Novel Method for Race Determination of Human Skulls Paper Authors: Casper Oakley, Li Bai, Iman Liao, Olasimbo Arigbabu, Nurliza Abdullah and Mohamad Helmee Mohamad Noor |
10:15 - 10:30 |
Anchored Kernel Hashing for Cancelable Template Protection for Cross-Spectrum Periocular Data Paper Authors: Kiran Raja, Raghavendra Ramachandra and Christoph Busch |
10:30 - 11:00 |
Coffee Break |
11:00 - 12:00 |
Saddok Kebairi Document Fraud : Reality And Challenge For Companies |
12:00 - 12:15 |
Categorization of Document Image Tampering Techniques and How to Identify Them Paper Authors: Francisco Cruz, Nicolas Sidère, Mickaël Coustaty, Vincent Poulain d'Andecy and Jean-Marc Ogier |
Overview
Recently, financial industry is featured with massive volumes of both structured and unstructured data, which are often associated with unlabeled and partially labeled data, or noisy and uncertain labels. Developing intelligent financial analysis and risk management tools for such data present major challenges for both practitioners and academic researchers. The proposed workshop mainly focuses on pattern recognition and machine learning methods such as kernel methods, feature selection, reinforcement learning, complex networks, deep learning methods, etc. for building intelligence for financial analysis and risk-based knowledge discovery.
Organizers
Lu Bai, Associate Professor, Central University of Finance and Economics, China
Luca Rossi, Assistant Professor Aston University, UK
Lixin Cui, Assistant Professor, Central University of Finance and Economics, China
Jian Tang, Assistant Professor, HEC Montreal & Montreal Institute for Learning Algorithms, Canada
Schedule
Venue: Room 301A
Time: 20thAugust 2018, 08:45 - 12:30 AM
SUBSLOT |
SPEAKER |
TITLE |
CHAIR |
08:45 - 09:10 |
Lixin Cui |
Opening Remarks Invited Talk 1: Feature Selection in P2P Lending Analysis |
Lu Bai |
09:10 - 09:50 |
Edwin Hancock |
Invited Talk 2: Exploring the Econo-physics of Market Networks using von Neumann Entropy |
Lu Bai |
09:50 - 10:30 |
Baogang Hu |
Invited Talk 3:Information Theoretic Learning in Pattern Classification |
Luca Rossi |
10:30 - 11:00 |
Coffee Break |
||
11:00 - 11:30 |
Ning Zhang |
Invited Talk 4: The New Generation of Artificial Intelligence in Finance |
Lixin Cui |
11:30 - 12:10 |
Francisco Escolano |
Invited Talk 5: An Information-Theoretic Approach for Graphs. |
Lixin Cui |
12:10 - 12:30 |
Lu Bai |
Invited Talk 6: A Preliminary Survey of Analyzing Dynamic Time-varying Financial Networks Using Graph Kernels |
Luca Rossi |
Overview
Following the success of the first workshop Reproducible Research on Pattern Recognition that held at the previous ICPR event 2016, this event will propose a new edition in continuation of the previous event with a new special focus on Digital Geometry and Mathematical Morphology. As for the previous edition, it is intended as both a participative short course on the basis of RR with open discussions with the attendants, and also as a practical workshop on how to do actual RR.
Organizers
Bertrand Kerautret Main Chair, LORIA, Université de Lorraine, Nancy
Miguel Colom CMLA, ENS Paris Saclay
Bart Lamiroy LORIA, Université de Lorraine, Nancy
Daniel Lopresti Lehigh University, Bethlehem, PA 18015
Pascal Monasse LIGM, Ecole des Ponts, Paris
Jean-Michel Morel CMLA, ENS Paris Saclay
Fabien Pierre LORIA, Université de Lorraine, Nancy
Hugues Talbot Center for Numerical Vision, CentraleSupelec, Paris
Schedule
Venue: Room 303 A
Time: 20thAugust 2018, 09:00 AM - 16:30 PM
SUBSLOT |
SPEAKER |
TITLE |
CHAIR |
09:00-10:00 |
Miguel Colom |
Invited Talk 1: Present and Future of the IPOL Journal: Machine Learning Applications. |
Daniel Lopresti |
10:00-10:40 |
Anguelos Nicolaou |
Paper 1: Non-deterministic Behavior of Ranking-based Metrics when Evaluating Embeddings. Authors: Anguelos Nicolaou, Sounak Dey, Vincent Christlein, Andreas Maier and Dimosthenis Karatzas |
Daniel Lopresti |
10:40 - 11:10 |
Coffee Break |
||
11:10-11 :50 |
Pascal Monasse |
Paper 2: A Root-to-Leaf Algorithm Computing the Tree of Shapes of an Image. Author: Pascal Monasse |
Bertrand Kerautret |
11:50-12:30 |
Phuc Ngo |
Paper 3: Discrete Regular Polygons for Digital Shape Rigid Motion via Polygonization. Authors: Phuc Ngo, Yukiko Kenmochi, Nicolas Passat and Isabelle Debled-Rennesson |
Bertrand Kerautret |
12:30-14:00 |
Lunch |
||
14:00-14:30 |
M. Colom B. Kerautret |
Invited Talk 2 |
Pascal Monasse |
14:30-15:30 |
M. Colom |
Practical session: Hands on the IPOL Demonstration System. |
Pascal Monasse |
15:30-16:00 |
Short papers authors |
Short Papers Fast track (and/or posters) |
Pascal Monasse |
16:00-16:30 |
Organizers |
Open discussion on the two previous editions of RRPR and on the future of the next Edition. |
Pascal Monasse |
W08 - 6th Visual observation and analysis of Vertebrate And Insect Behavior workshop (VAIB18)
Overview
There has been an enormous amount of research on analysis of video data of humans, but relatively little on visual analysis of other organisms. The goal of this workshop is to stimulate and bring together the current research in this area, and provide a forum for researchers to share expertise. As we want to make this more of a discussion workshop, we encourage work-in-progress presentations. Reviewing will be lightweight and only abstracts will be circulated to attendees. The issues that the research will address include: detection of living organisms, organism tracking and movement analysis, dynamic shape analysis, classification of different organisms (eg. by species), assessment of organism behavior or behavior changes, size and shape assessment, counting, health monitoring, These problems can be applied to a variety of species at different sizes, such as fruit and house flies, crickets, cockroaches and other insects, farmed and wild fish, mice and rats, commercial farm animals such as poultry, cows and horses, and wildlife monitoring, etc. One aspect that they all have in common is video data.
Organizers
Robert Fisher University of Edinburgh
John Hallam University of South Denmark
Simone Palazzo Universita' di Catania
Schedule
Venue: Room 303B
Time: 20th August 2018, 09:00 – 12:30 AM
SUBSLOT |
SPEAKER |
TITLE |
CHAIR |
09:00 - 09:30 |
O. Mothes |
Multi-view Anatomical Animal Landmark Localization using Deep Feature Regression |
Fisher |
09:30 - 10:00 |
A. Gostler |
Tracking Golden-Collared Manakins in the Wild |
Fisher |
10:00 - 10:30 |
L. N. Govindarajan |
Neural Computing on a Raspberry Pi: Applications to Zebrafish Behavior Monitoring |
Fisher |
10:30 - 11:00 |
Coffee Break |
||
11:00 - 11:30 |
I. F. Rodriguez |
Multiple Animal Tracking in Video Using Part Affinity Fields |
Fisher |
11:30 - 12:00 |
F. Naiser |
Tracking and Re-Identification System for Multiple Laboratory Animals |
Fisher |
12:00 - 12:30 |
M. C. Bakkay |
Support Vector Machine (SVM) Recognition Approach adapted to Individual and Touching Moths Counting in Trap Images |
Fisher |
W09 - 5th IAPR TC 9 Workshop on Multimodal Pattern Recognition of Social Signals in Human Computer Interaction (MPRSS 2018)
Overview
Building intelligent artificial companions capable to interact with humans in the same way humans interact with each other is a major challenge in affective computing. Such a type of interactive companion must be capable of perceiving and interpreting multimodal information about the user in order to be able to produce an appropriate response. The proposed workshop mainly focuses on pattern recognition and machine learning methods for the perception of the user’s affective states, activities and intentions.
Organizers
Friedhelm Schwenker Institute of Neural Information Processing, Ulm University, Germany
Stefan Scherer Institute for Creative Technologies, University of Southern California, USA
Schedule
Venue: Room 302B
Time: 20thAugust 2018, 14:00 – 17:30 PM
SUBSLOT |
SPEAKER |
TITLE |
CHAIR |
|
Registration |
||
14:00-14:05 |
Opening of MPRSS 2018 |
Scherer / Schwenker |
|
14:05-14:20 |
Friedhelm Schwenker |
Multimodal Recognition of Mental States : Emotions, Affect, and Pain |
TBA |
14:20-15:05 |
Xiaojun Wu Jiangnan University |
Invited Talk: Light weight deep neural networks with applications to pattern recognition |
Schwenker / Scherer |
15:05-15:30 |
Suzan Anewar |
Perceptual judgments to detect computer generated forged faces in social media |
TBA |
15:30-16:00 |
Coffee Break |
||
16:00-16:25 |
Girmaw Abele |
A first-person vision dataset of office activities |
TBA |
16:25-16:50 |
Xinyi Liu |
An image captioning method for infant sleeping environment diagnosis |
X. Wu |
16:50-17:15 |
Patrick Thiam |
Combining deep and hand crafted features for audio-based pain intensity classification |
Milanova |
17:15-17:30 |
Closing of MPRSS 2018: Discussion, Proceedings, Special Issue, etc |
Additional Information
Workshop Website:https://neuro.informatik.uni-ulm.de/MPRSS2018/
W10 – Deep Learning for Document Analysis and Recognition
Overview
The technology of document analysis and recognition (DAR) aims to automatically extract information from document images and handwriting by analyzing the structure and textual contents. It has tremendous applications such as digitization of books and financial notes and information extraction from Web document images. Recognizing text from images, known as Optical Character Recognition (OCR) is the core task of DAR. Recently, OCR has achieved a great success in both scientific research and practical application for different scenes. A traditional OCR system is heavily pipelined, with hand-designed and highly-tuned modules, usually composed of line extraction, word detection, letter segmentation, and then applying different techniques to each piece of a character to figure out what the character is. Nowadays, we have entered a new era of big data, which offers both opportunities and challenges to the field of OCR and DAR. We should seek new OCR and DAR methods to be adaptive to big data, and also push forward new OCR and DAR applications benefited from big data.
Deep learning, which is considered as one of the most significant breakthrough in recent pattern recognition and computer vision fields, has greatly affected these fields and achieved impressive progress in both academy and industry. Currently, deep learning is widely accepted as an effective OCR solution, which first learns to detect text lines or words from images, then recognize the sequence of characters directly from extracted text lines or words. The hand-built and highly tuned modules are avoided in the deep learning-based OCR system. It is expected that the development of deep learning theories and applications would further influence the field of OCR and DAR.
Organizers
Yongpan Wang Alibaba Group, China
Xiang Bai Huazhong University of Science and Technology, China
Cheng-Lin Liu Institute of Automation of Chinese Academy of Sciences, China
Schedule
Venue: Room 305
Time: 20thAugust 2018, 14:10 – 17:40 PM
SUBSLOT |
SPEAKER |
TITLE |
14:10 - 14:30 |
Simone marinai |
Reflections around Deep Learning and Document Image Analysis |
14:30 - 14:50 |
Lianwen Jin |
Toward High Performance Unconstrained Online Handwritten Chinese Text Recognition: A Deep Learning Approach |
14:50 - 15:10 |
Yongpan Wang |
the Duguang cloud system of Alibaba:Development and challenges for Application of OCR |
15:10 - 15:30 |
C V Jawahar |
Deep Learning Revisiting Handwriting: LetNet to HWNet |
15:30 - 16:00 |
Coffee Break |
|
16:00 - 16:20 |
Weilin Huang |
Reading Text in the Wild: From Text Detection to End-to-End Recognition |
16:20 - 16:40 |
Huasha Zhao |
Multimodal information extraction using deep learning technologies |
16:40 - 17:40 |
Panel |
Future trends on deep learning for OCR and DAR |
Overview
The MIPPSNA 2018 workshop aims to compile the latest research advances on the analysis of multimodal information for facing problems that are not visually obvious, this is, problems for which the sole visual analysis is insufficient to provide a satisfactory solution. Specifically, two problems are of interest for the workshop: personality analysis and social behavior analysis, although submissions in related topics will be considered as well. The workshop is associated to an ICPR contest running two tracks in the same topics, see http://chalearnlap.cvc.uab.es/challenge/27/description/. Therefore, the workshop also accepts submissions from contest participants describing their solutions for the challenge.
Organizers
Hugo Jair Escalante INAOE, Mexico, ChaLearn, USA
Esaú Villatoro UAM-C, Mexico
Bogdan Ionescu University Politehnica of Bucharest, Romania
Gabriela Ramírez UAM-C, Mexico
Sergio Escalera CVC-UAB
Martha Larson Multimedia Information Retrieval Lab Delft University of
Technology, Netherlands
Henning Müller University of Applied Sciences Western Switzerland (HES-SO),
Switzerland
Isabelle Guyon ChaLearn, USA, Université Paris Saclay, France
Schedule
Venue: Room 302A
Time: 20thAugust 2018, 09:00 - 12:20 AM
SUBSLOT |
SPEAKER |
TITLE |
CHAIR |
09:00 - 09:10 |
Esaú Villatoro |
Welcome – Workshop opening |
Hugo Jair Escalante |
09:10 - 09:55 |
Invited speaker Sergio Escalera |
Apparent Personality Computing |
Hugo Jair Escalante |
09:55 - 10:15 |
Gabriela Ramírez |
Overview of the Multimedia Information Processing for Personality & Social Networks Analysis Contest. Gabriela Ramírez, Esaú Villatoro, Bogdan Ionescu, Hugo Jair Escalante, Sergio Escalera, Martha Larson, Henning Müller, and Isabelle Guyon |
Hugo Jair Escalante |
10:15 - 10:30 |
Ernesto Pérez Costa |
Recognition of Apparent Personality traits from text and handwritten images. Ernesto Pérez Costa, Luis Viilaseñor-Pienda, Eduardo Morales, and Hugo Jair Escalante |
Hugo Jair Escalante |
10:30 - 11:00 |
Break |
Coffee Break |
Break |
11:00 - 11:20 |
Hiram Calvo |
Handwritten texts for Personality Identification Using Convolutional Neural Networks. José E. Valdez-Rodríguez, Hiram Calvo, Edgardo M. Felipe-Riverón |
Esaú Villatoro |
11:20 - 11:40 |
Egils Avots |
Multimodal Database of Emotional Speech, Video and Gestures. Tomasz Sapinski, Dorota Kaminska, Adam Pelikant, Cagri Ozcinar, Egils Avots, and Gholamreza Anbarjafari |
Esaú Villatoro |
11:40 - 12:00 |
Rodrigo Rill |
From Text to Speech: A Multimodal Cross-domain Approach for Deception Detection. Rodrigo Rill-García, Luis Villaseñor-Pineda, Verónica Reyes-Meza, and Hugo Jair Escalante |
Esaú Villatoro |
12:00 - 12:20 |
Hugo Jair Escalante |
Farewell– Workshop closing and announcements |
Esaú Villatoro |