Juan D. Gutiérrez | i3 lab

MetrikaBox: An open framework for experimenting with audio classification

Thu, 28 Aug 2025 00:00:00 +0000

Prompt Once, Segment Everything: Leveraging SAM 2 Potential for Infinite Medical Image Segmentation with a Single Prompt

Mon, 14 Apr 2025 00:00:00 +0000

Beyond Spectrograms: Rethinking Audio Classification from EnCodec's Latent Space

Sun, 16 Feb 2025 00:00:00 +0000

Advancing precision in medical image segmentation: A performance analysis of loss functions for COVID-19 lung infection segmentation in computed tomography images

Fri, 01 Nov 2024 00:00:00 +0000

Analysis of ChatGPT Performance in Computer Engineering Exams

Mon, 25 Mar 2024 00:00:00 +0000

No More Training: SAM's Zero-Shot Transfer Capabilities for Cost-Efficient Medical Image Segmentation

Mon, 15 Jan 2024 00:00:00 +0000

JENUI 2023: best paper

Thu, 06 Jul 2023 00:00:00 +0000

On November 30, 2022, OpenAI introduced ChatGPT. Like most of us, we were surprised 🤯 with its incredible capabilities. From the first moment, we wondered what impact it would have on the different facets of our day-to-day life: in Computer Engineering, research, and teaching. Based on an idea from our colleague Roberto, we decided to focus on the latter.

The result of several months of effort is our work “Impact of ChatGPT in the evaluation methods of a Computer Engineering degree “, which we presented to the JENUI of 2023 and for which we have been awarded the prize for best paper of the conference. In this edition, dominated by ChatGPT (something that has kept some speakers awake at night), the paper “To rival or not: analysis of Wooclap’s competition mode based on performance and audio processing “, by our colleagues from the University of Murcia, was also awarded.

Here you can see Roberto presenting our experience to the rest of the attendees (about 10 minutes plus question time):

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We will share the proceedings as soon as they are published so you can read the work and give us your feedback. In the meantime, here is the abstract:

Generative Artificial Intelligence has undergone an essential evolution during the last years and especially in 2022. One of the intelligence that has caused the most buzz in academia is ChatGPT, which provides an interface that significantly simplifies the productive use of a large language model. These language models can parse and generate text with great speed and quality. These capabilities could have a relevant impact on teaching-learning methodologies and assessment methods. In order to analyze the possible impact of ChatGPT on assessment methods, in this work, ChatGPT’s ability to solve the exams of 15 Software Engineering subjects of a Computer Engineering degree has been tested. The results show that ChatGPT could noticeably impact the assessment methods; it can overcome many questions and problems of different natures in multiple subjects. As a fundamental contribution, a detailed study of the results by type of questions and problems is provided, which allows us to establish recommendations to be taken into account in the design of assessment methods.

Are you interested in the subject? Do you want to collaborate with us? Contact us, and we’ll talk.

Update: You can read the cited work right here.

Impacto de ChatGPT en los métodos de evaluación de un grado de Ingeniería Informática

Wed, 05 Jul 2023 00:00:00 +0000

ADAPIMMA

Tue, 04 Jul 2023 11:31:59 +0200

Copyright management in Spain is an issue that has always been in the eye of the hurricane and that has aroused great controversy. Special mention deserves the management of copyrights of musical pieces. The SGAE (General Society of Authors and Publishers) monopolizes managing these rights. Copyright management is governed by the Intellectual Property Law, which in its wording from 1996, is somewhat vague regarding distribution criteria. The wording could be more precise. It needs to be clarified how the SGAE rates the issuing entities, such as the radio. In some cases, it is done by the billing volume of the issuing entity, applying a percentage. In other words, it is independent of the music used by the station, and, this being the case, there is no way to make a fair distribution among the authors who contribute that music. In other cases, estimates are made for the use of the music, and based on that, the management company bills. This can lead to situations where talented young authors with short and unconsolidated careers need to receive adequate rewards for their work and discourage them from continuing their careers in this field.

Precisely the objective of this project is to investigate the techniques that would allow the development of a system capable of i) discriminating the use made of music in radio media according to its cataloging in the new Intellectual Property Law (solution to the first problem) and ii ) associate the exact use made of the piece of music to its original author in order to make an equitable distribution of royalties (solution to the second problem). The development of this proposal would mean a significant innovation in the musical world that could be an essential source, not only of potential clients worldwide but also of international investments that allow the internationalization of the ICT model of Extremadura, both fundamental lines of the Employment axis, Entrepreneurship and Innovation of the Regional Green and Circular Economy Strategy, Extremadura 2030. Not surprisingly, due to its evolution and potential path in Extremadura, the ICT sector is an active pole of production of transversal technology and a motor for the establishment of software development companies, which can be considered green companies as they do not generate waste.

Results

The paper “A Hybrid Multidimensional Recommender System for Radio Programs”, published in the Elsevier’s “Expert Systems with Applications”, is a direct result of this project.

It’s source code is available in GitHub via two projects:

A demo is also available.

SAM in Medical Image Segmentation

Tue, 23 May 2023 15:00:53 +0200

The project’s source code can be found in this repository.

MusicGenia

Fri, 12 May 2023 13:17:36 +0200

MusicGenia’s main goal consists in building a cloud-based platform to offer AI-generated production music as a service for content creators and media, which can be consumed online (live music generation) or offline (recorded music generation). The direct benefits of that platform are: (1) music free of royalties; (2) original music; (3) easy to find music suiting your content; and (4) music on stream (consume as much as you need, pay per seconds not per song).

A Model-Driven Approach for Systematic Reproducibility and Replicability of Data Science Projects

Tue, 28 Jun 2022 00:00:00 +0000

CompareML: A Novel Approach to Supporting Preliminary Data Analysis Decision Making

Wed, 01 Jun 2022 00:00:00 +0000

A Hybrid Multidimensional Recommender System for Radio Programs

Sat, 20 Feb 2021 00:00:00 +0000

Towards a Conceptual Framework for the Specification of Reproducible and Replicable Data Analysis Projects

Fri, 01 Jan 2021 00:00:00 +0000