AgriAI’23 Call for paper

We cordially invite you to submit your original contributions to AgriAI'23 – the 1st International Workshop on AI in Agriculture,

which will take place as a satellite workshop to IEEE FedCSIS 2023, to be held in Warsav, Poland on Septemeber 17 – 20, 2023.
Please see the workshop website: https://fedcsis.org/sessions/aaia/agriai  and the general conference web page  https://fedcsis.org/  for more information.

Paper submission deadline: May 23, 2023

Artificial Intelligence (AI) is increasingly used in agriculture for a variety of uses, from plant disease detection to weeding automation, soil status monitoring, crop prediction, irrigation management, and decreased use of resources for improving quality and productivity. This workshop welcomes contributions related to a wide variety of interdisciplinary research and applications related to artificial intelligence in agriculture. AI can, in fact, provide highly positive effects on precision agriculture by optimizing, automating and forecasting several aspects of farming and revolutionizing the sector, providing helpful information and driving decisions using multiple sources of data and different sensors.

Moreover, in the climate change era, AI can improve sustainability by optimizing the use of resources such as water and soil management. We welcome innovative contributions, early results and position papers addressing one or more of the topics listed below and intend to foster informal discussions and bring together researchers, practitioners and industry experts to explore the challenges and opportunities of AI and Agriculture. We look forward to receiving your submissions and seeing you at the workshop!

Topics

Papers related to theories, methodologies, and applications in science and technology in the field of AI in Agriculture are especially solicited. Topics covering applications and academic research are included, but not limited to:

  • Computer vision in agriculture
  • Signal and image processing in agriculture
  • Computational intelligence in agriculture
  • Artificial intelligence in agriculture
  • Decision support systems
  • Expert systems & predictive systems
  • AI-based precision agriculture
  • Machine learning and pattern recognition
  • IoT in agriculture
  • Food and livestock management
  • Big data
  • Remote sensing
  • Unmanned aerial vehicle vehicles
  • Autonomous driving in agriculture
  • Harvesting automation
  • Robotics and robotic perception in agriculture
  • Ethics and social impact of AI on agriculture
  • AI-based crowd-sensing and participatory approaches in agriculture
  • Applications in agriculture
     

Submission rules

  • Authors should submit their papers as Postscript, PDF or MSWord files.
  • The total length of a paper should not exceed 10 pages IEEE style (including tables, figures and references). IEEE style templates are available at https://www.fedcsis.org/2020/instructions
  • Papers will be refereed and accepted on the basis of their scientific merit and relevance to the workshop.
  • Preprints containing accepted papers will be published on a USB memory stick provided to the FedCSIS participants.
  • Only papers presented at the conference will be published in Conference Proceedings and submitted for inclusion in the IEEE Xplore® database.
  • Conference proceedings will be published in a volume with ISBN, ISSN and DOI numbers and posted at the conference WWW site.
  • Conference proceedings will be submitted for indexation according to information at https://fedcsis.org/for_authors/indexation
  • Organizers reserve right to move accepted papers between FedCSIS technical sessions.

Technical Session Chairs

  • Massimo Martinelli, Institute of Information Science and Technologies, National Research Council of Italy, Pisa, Italy
  • Davide Moroni, Institute of Information Science and Technologies, National Research Council of Italy, Pisa, Italy
  • Ales Procházka, University of Chemistry and Technology & Czech Technical University CIIRC, Prague, Czech Republic
  • Karel Charvat, Czech Center for Science and Society, Prague, Czech Republic

Program Committee

  • Bacco, Manlio, Institute of Information Science and Technologies, National Research Council, Pisa, Italy
  • Berton, Andrea, Geosciences and Earth Resources, National Research Council, Pisa, Italy
  • Dahyot, Rozenn, Maynooth University Department of Computer Science, Dublin, Ireland
  • Ienco, Dino, Territories, Environment, Remote Sensing and Spatial Information, Montpellier, France
  • Klapp, Iftach, Institute of Agricultural Engineering, Volcani Institute, Agricultural Research Organization Bet Dagan, Tel Aviv, Israel
  • Milella, Annalisa, Institute of Intelligent and Industrial Technologies and Systems for Advanced Manufacturing, National Research Council, Bari, Italy
  • Mildorf, Tomas, University of West Bohemia, Pilsen, Czech Republic
  • Majdik, András, Lászlóm, Institute for Computer Science and Control, Budapest, Hungary
  • Nutini, Francesco, Institute for Electromagnetic Sensing of the Environment, National Research Council, Milano, Italy
  • Palma, Raul, Supercomputing and Networking Center, Poznan, Poland
  • Salvetti, Ovidio, Institute of Information Science and Technologies, National Research Council, Pisa, Italy
  • Scozzari, Andrea, Institute of Information Science and Technologies, National Research Council, Pisa, Italy
  • Stavness, Ian, Department of Computer Science, Global Institute for Food Security, University of Saskatchewan, Saskatoon, Canada
  • Töreyin, Behçet Uğur, Technical University, Istanbul, Turkey
  • Toscano, Piero, Institute of Bioeconomy, National Research Council, Florence, Italy
  • Trocan, Maria, Institut Supérieur d'Electronique de Paris, Paris, France
  • Zerubia, Josiane, National Institute for Research in Digital Science and Technology, Sophia Antipolis, France

Fwd: [CVML] 3DHumans Dataset Release -Free high quality human mesh data with diverse clothing for research.

Dear all, 

I would like to announce the release of our new high quality “3DHumans” dataset for Human Body Models with rich geometry and textural details as well as loose oriental clothing.  The 3DHumans dataset provides around 180 meshes of people in diverse body shapes in various garments styles and sizes. We cover a wide variety of clothing styles, ranging from loose robed clothing, like saree (a typical South-Asian dress) to relatively tight fit clothing, like shirts and trousers. Along with the high quality geometry (mesh) and texture map, we also provide registered SMPL and semantic segmentation. The faces of the subjects are blurred and smoothened out to maintain privacy of volunteers.

The dataset is collected using Artec Eva hand held structured light scanner. The scanner has 3D point accuracy up to 0.1 mm and 3D resolution of 0.5 mm, enabling capture of high frequency geometrical details, alongwith high resolution texture maps. The subjects were scanned in a studio environment with controlled lighting and uniform illumination.

Please visit our webpage to access our 3DHumans dataset: http://cvit.iiit.ac.in/research/projects/cvit-projects/3dhumans
Please refer to our group webpage for related research papers with focus on Human Body Digitization, Learnable Texture Mapping, Garment Digitization, 4D Dynamic capture of Humans. We are open to academic and industrial collaboration for propelling research in 3D Vision domains. A high quality dynamic motion capture data with rich 3D geometry is also planned to be released in the upcoming months. We are also hiring research students, RA to our group so feel free to apply. 
Please reach out to us if you have query related to dataset on asharma<AT>iiit<DOT>ac.in
Thanks,
Avinash Sharma
CVIT, IIIT Hyderabad, INDIA

IEEE CBMS 2023 – CALL FOR PAPERS

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36th IEEE International Symposium on Computer Based Medical Systems
L’Aquila, Italy, 22-24 June 2023

https://2023.cbms-conference.org/

Call for Articles – International Journal of Chaos, Control, Modelling and Simulation (IJCCMS)

13 al 17 de Marzo: “Semana de la Computación de Alto Desempeño, Datos y Arquitecturas”

La “Semana de la Computación de Alto Desempeño, Datos y Arquitecturas” es una escuela integral de Computación de Alto Desempeño (HPC), nuevas arquitecturas de cómputo y procesamiento de grandes volúmenes de datos.

Se plantea la realización simultánea de cinco tracks/recorridos que apuntan a distintas formaciones y necesidades de estudiantes de grado y posgrado. Uno de los tracks está específicamente orientado a quienes quieran aprender/perfeccionar sobre administración de clusters.

Hoy en día, no hay una oferta de cursos ni a nivel introductorio ni avanzado o de actualización en Computación de Alto Desempeño (HPC) como lo que se propone en esta escuela.

Se dictará en los laboratorios y aulas del nuevo pabellón 0+infinito en Ciudad Universitaria (CABA) en jornada completa de lunes a viernes.
Los cursos se darán por la mañana de 9 a 12 y por la tarde de 14 a 17. Entre las 18:00hs y las 20:00hs se darán actividades y charlas de interés para estudiantes de todos los tracks.

Se contará con un plantel único de profesores invitados agrupados en los siguientes tracks:

T1: Fundamentos de programación paralela.
– Fundamentos de computación (Dr. Sergio Nesmachnow – Universidad de la República, Uruguay) 12 horas de clase
– Cómputo con GPU (Dr. Pablo Ezzatti – Universidad de la República, Uruguay) 9 horas de clase
– Paralelismo de tareas: escalabilidad más allá de MPI, Legion, StarPU, OmpSs, Charm++ (Dr. Esteban Meneses – Centro Nacional de Alta Tecnología, Costa Rica) 9 horas de clase

T2: Técnicas y herramientas avanzadas de simulación paralela.
– Fundamentos del set de herramientas ADIOS (Dr. Scott Klasky, Oak Ridge National Laboratory, Estados Unidos) 6 horas de clase
– Visualización (Dr. Podhorszki, Oak Ridge National Laboratory, Estados Unidos) 9 horas de clase
– Reducción de datos (Dr. Pugmire, Oak Ridge National Laboratory, Estados Unidos) 9 horas de clase
– Taller integrador (Dr. Klasky, Dr. Podhorszki, Dr. Pugmire, Oak Ridge National Laboratory, Estados Unidos) 6 horas de clase

T3: Herramientas de procesamiento de grandes volúmenes de datos y machine learning.
– Computación en la Nube (Prof. Robinson Rivas-Suarez, Universidad Central de Venezuela, Venezuela) 15 horas
– Computación de alta perfomance interactiva e inteligencia artifical con Jupyter (Dr. Göbbert, Jülich Supercomputing Centre, Alemania) 15 horas

T4: Nuevas arquitecturas y plataformas de cómputo.
– Diseño ágil de Systems-On-Chip programables: aplicación a vehículos autónomos conectados (Dr. Augusto Vega, IBM Watson Research Center, Estados Unidos) 12 horas
– Arquitecturas para la aceleración de compresión de imágenes y video (Dr. Mario Kovac, University of Zagreb, Croacia) 12 horas
– Desarrollo de aceleradores para las plataformas de computación adaptiva (Dr. Mario Ruiz Noguera, AMD) 6 horas

T5: Herramientas y técnicas de administración de plataformas de cómputo.
– Operación de una Cloud privada basada en OpenStack (Dr. Maximiliano Geier, Max Planck Computing and Data Facility, Alemania) 12 horas
– RESTful API para HPC (Ing. Alejandro Dabin, Swiss National Supercomputing Centre, Suiza) 9 horas
– HPC containers (Ing. Juan Pablo Dorsch, Swiss National Supercomputing Centre, Suiza) 9 horas

*IMPORTANTE*: se contará con becas de traslado y viáticos diarios a cargo del Sistema Nacional de Cómputo de Alto Rendimiento para estudiantes de grado y posgrado residentes en Argentina a más de 100km de CABA. Se dará prioridad a las postulaciones de estudiantes mujeres y minorías cómo integrantes de la comunidad travesti trans y personas con discapacidad.

En breve se abrirá un formulario de pre-inscripción, las vacantes están limitadas por la capacidad de las aulas.

Un sitio web en desarrollo con información se puede encontrar en ecar2023.hpclatam.org.

Es un área que brinda muy buenas oportunidades de desarrollo, es una gran oportunidad para acercarse así que ¡alentamos que lo hagan!

Más información ecar2023@dc.uba.ar / emocskos@dc.uba.ar

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