SI-Lab Annual Research Report 2021

2021

The Signal & Images Laboratory (SI-Lab) is an interdisciplinary research group in computer vision, signal analysis, smart vision systems and multimedia data understanding. It is part of the Institute for Information Science and Technologies of the National Research Council of Italy. This report accounts for the research activities of the Signal and Images Laboratory of the Institute of Information Science and Technologies during the year 2020

2001

Abstract DataLab-J is a software signal and image processing laboratory which has proved effective both as an educational" workbench" and in practical operational use. It requires a pedagogical tool, a research environment, and a fully operational data analysis system, ie, it is used not only in undergraduate engineering courses, but in graduate study and general research.

IEEE Transactions on Education, 2002

The techniques of digital signal processing (DSP) and digital image processing (DIP) have found a myriad of applications in diverse fields of scientific, commercial, and technical endeavor. DSP and DIP education needs to cater to a wide spectrum of people from different educational backgrounds. This paper describes tools and techniques that facilitate a gentle introduction to fascinating concepts in signal and image processing. Novel LabVIEW-and MATLAB-based demonstrations are presented, which, when supplemented with Web-based class lectures, help to illustrate the power and beauty of signal and image-processing algorithms. Equipped with informative visualizations and a user-friendly interface, these modules are currently being used effectively in a classroom environment for teaching DSP and DIP at the University of Texas at Austin (UT-Austin). Most demonstrations use audio and image signals to give students a flavor of real-world applications of signal and image processing. This paper is also intended to provide a library of more than 50 visualization modules that accentuate the intuitive aspects of DSP algorithms as a free didactic tool to the broad signal and image-processing community.

Frontiers in Education, 2003. …, 2003

Index Ternis - Java, On-line Laboratories, Two-dimensional Signal Processing, Web. ... Distance learning is very active at Arizona State University (ASU) with high enrollment of students from local companies. Although many existing educational software tools [I]-[SI were ...

BioTechniques, 2006

Relying on Computers Given the incredible advances in laboratory science in the last quarter of a century, it may seem that what the lab of the future will look like is anyone's guess. However, because those advances have included the ability to generate an astounding amount of data, a common theme for the lab of the future is continued, if not increased, reliance on computers. For Katherine Peterson, a staff scientist at the National Eye Institute (NEI) at the National Institutes of Health (NIH), Bethesda, MD, the lab of the future will need to do a better job of multidisciplinary integration. "You can't putter away by yourself anymore in the present mode of data collection," she observes. Integration of teams of people in day-today operations will be more to everyone's benefit. She

Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2002

AGILE (Light Imager for Gamma-ray Astrophysics) is a small scientific satellite for the detection of cosmic g-ray sources in the energy range 30 MeV-50 GeV with a very large field of view (1/4 of the sky). It is planned to be operational in the years 2003-2006, a period in which no other g-ray mission in the same energy range is foreseen.

Image Communications and Workstations, 1990

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2004

Welcome to the Eleventh Annual C.A.S.I.S. Workshop, a yearly event at the Lawrence Livermore National Laboratory, presented by the Center for Advanced Signal & Image Sciences, or CASIS, and sponsored by the LLNL Engineering Directorate. Every November for the last 10 years we have convened a diverse set of engineering and scientific talent to share their work in signal processing,

Digital Image processing is a topic of great relevance for practically any project, either for basic arrays of photodetectors or complex robotic systems using artificial vision. It is an interesting topic that offers to multimodal systems the capacity to see and understand their environment in order to interact in a natural and more efficient way. The development of new equipment for high speed image acquisition and with higher resolutions requires a significant effort to develop techniques that process the images in a more efficient way. Besides, medical applications use new image modalities and need algorithms for the interpretation of these images as well as for the registration and fusion of the different modalities, so that the image processing is a productive area for the development of multidisciplinary applications. The aim of this chapter is to present different digital image processing algorithms using LabView and IMAQ vision toolbox. IMAQ vision toolbox presents a complet...

arXiv (Cornell University), 2022

In the CMS experiment at CERN, Geneva, a large number of HGCAL sensor modules are fabricated in advanced laboratories around the world. Each sensor module contains about 700 checkpoints for visual inspection thus making it almost impossible to carry out such inspection manually. As artificial intelligence is more and more widely used in manufacturing, traditional detection technologies are gradually being intelligent. In order to more accurately evaluate the checkpoints, we propose to use deep learning-based object detection techniques to detect manufacturing defects in testing large numbers of modules automatically.