Juan D. Gutiérrez | INTIA

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 people, it caught us by surprise 🤯 with its incredible capabilities. From the very first moment we wondered what impact it would have on the different aspects of our daily lives: in Computer Engineering, in research and in teaching. From an idea proposed by our colleague Roberto, we decided to focus on the latter.

The result of several months of effort is our paper “Impact of ChatGPT on the evaluation methods of a Computer Engineering degree”, which we submitted to JENUI 2023 and for which we were awarded the best paper prize at the conference. In this edition, dominated by ChatGPT (something that has kept some speakers awake at night), the paper “Compete 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 conference attendees (about 10 minutes plus the Q&A session):

As soon as the proceedings are published we will share them so you can read the paper and give us your opinion. In the meantime, here is the abstract:

Generative Artificial Intelligences have experienced significant evolution in recent years and, especially, in 2022. One of the AIs that has caused the most stir in the academic world is ChatGPT, which provides an interface that greatly simplifies the productive use of a large language model. These language models are capable of analyzing and generating texts with great speed and quality. These capabilities could have a relevant impact on teaching-learning methodologies and also on evaluation methods. In order to analyze the possible impact of ChatGPT on evaluation methods, in this work, ChatGPT’s ability to solve exams from 15 Software Engineering courses in a Computer Engineering degree has been tested. The results show that ChatGPT could have a clear impact on evaluation methods; as it is capable of passing a significant number of questions and problems of different nature in multiple courses. As a main contribution, a detailed study of the results by question and problem typology is provided, which allows establishing recommendations to be taken into account in the design of evaluation methods.

Interested in the topic? Want to collaborate? Get in touch with us and let’s talk.

Update: You can read the cited paper right here.

Impact of ChatGPT on the evaluation methods of a Computer Engineering degree

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

ADAPIMMA

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

Copyright management in Spain has always been a hot-button issue that has sparked great controversy. Special mention deserves the management of copyright for musical pieces. To manage these rights there is SGAE (General Society of Authors and Publishers) which maintains a certain monopoly. Copyright management is governed by the Intellectual Property Law, which in its 1996 version is somewhat vague regarding distribution criteria. So vague is the wording that it is not clear how SGAE charges broadcasting entities, such as radio stations. In some cases it is done based on the billing volume of the broadcasting entity, applying a percentage. That is, it is independent of the music used by the station and, being so, there is no way to make a fair distribution among the authors who provide that music. In other cases, estimates of music usage are made and based on that the management company bills. This can produce situations where young talented authors with short and less established careers are not receiving adequate compensation for their work and may be discouraged from continuing their career in this field.

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

Results

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

Its source code is available through two GitHub projects:

A demo is also available.

SAM for medical image segmentation

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

The source code for this project is located 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