201 citations · 919 across the 35 of their papers we have counts for
38 papers
Probing Perfection: The Relentless Art of Meddling for Pulmonary Airway Segmentation from HRCT via a Human-AI Collaboration Based Active Learning Method
Shiyi Wang, Yang Nan, Sheng Zhang +6
In pulmonary tracheal segmentation, the scarcity of annotated data is a prevalent issue in medical segmentation. Additionally, Deep Learning (DL) methods face challenges: the opaci…
AiGAS-dEVL: An Adaptive Incremental Neural Gas Model for Drifting Data Streams under Extreme Verification Latency
Maria Arostegi, Miren Nekane Bilbao, Jesus L. Lobo +1
The ever-growing speed at which data are generated nowadays, together with the substantial cost of labeling processes cause Machine Learning models to face scenarios in which data…
Forward-Forward Learning achieves Highly Selective Latent Representations for Out-of-Distribution Detection in Fully Spiking Neural Networks
Erik B. Terres-Escudero, Javier Del Ser, Aitor Martínez-Seras +1
In recent years, Artificial Intelligence (AI) models have achieved remarkable success across various domains, yet challenges persist in two critical areas: ensuring robustness agai…
Emerging NeoHebbian Dynamics in Forward-Forward Learning: Implications for Neuromorphic Computing
Erik B. Terres-Escudero, Javier Del Ser, Pablo García-Bringas
Advances in neural computation have predominantly relied on the gradient backpropagation algorithm (BP). However, the recent shift towards non-stationary data modeling has highligh…
Evolutionary Computation for the Design and Enrichment of General-Purpose Artificial Intelligence Systems: Survey and Prospects
Javier Poyatos, Javier Del Ser, Salvador Garcia +6
In Artificial Intelligence, there is an increasing demand for adaptive models capable of dealing with a diverse spectrum of learning tasks, surpassing the limitations of systems de…
Overlap Number of Balls Model-Agnostic CounterFactuals (ONB-MACF): A Data-Morphology-based Counterfactual Generation Method for Trustworthy Artificial Intelligence
José Daniel Pascual-Triana, Alberto Fernández, Javier Del Ser +1
Explainable Artificial Intelligence (XAI) is a pivotal research domain aimed at understanding the operational mechanisms of AI systems, particularly those considered ``black boxes'…
When AI Eats Itself: On the Caveats of AI Autophagy
Xiaodan Xing, Fadong Shi, Jiahao Huang +8
Generative Artificial Intelligence (AI) technologies and large models are producing realistic outputs across various domains, such as images, text, speech, and music. Creating thes…
Managing the unknown: a survey on Open Set Recognition and tangential areas
Marcos Barcina-Blanco, Jesus L. Lobo, Pablo Garcia-Bringas +1
In real-world scenarios classification models are often required to perform robustly when predicting samples belonging to classes that have not appeared during its training stage.…
Efficient Object Detection in Autonomous Driving using Spiking Neural Networks: Performance, Energy Consumption Analysis, and Insights into Open-set Object Discovery
Aitor Martinez Seras, Javier Del Ser, Pablo Garcia-Bringas
Besides performance, efficiency is a key design driver of technologies supporting vehicular perception. Indeed, a well-balanced trade-off between performance and energy consumption…
Using Curiosity for an Even Representation of Tasks in Continual Offline Reinforcement Learning
Pankayaraj Pathmanathan, Natalia Díaz-Rodríguez, Javier Del Ser
In this work, we investigate the means of using curiosity on replay buffers to improve offline multi-task continual reinforcement learning when tasks, which are defined by the non-…
Enhanced Generalization through Prioritization and Diversity in Self-Imitation Reinforcement Learning over Procedural Environments with Sparse Rewards
Alain Andres, Daochen Zha, Javier Del Ser
Exploration poses a fundamental challenge in Reinforcement Learning (RL) with sparse rewards, limiting an agent's ability to learn optimal decision-making due to a lack of informat…
General Purpose Artificial Intelligence Systems (GPAIS): Properties, Definition, Taxonomy, Societal Implications and Responsible Governance
Isaac Triguero, Daniel Molina, Javier Poyatos +2
Most applications of Artificial Intelligence (AI) are designed for a confined and specific task. However, there are many scenarios that call for a more general AI, capable of solvi…
ChatAgri: Exploring Potentials of ChatGPT on Cross-linguistic Agricultural Text Classification
Biao Zhao, Weiqiang Jin, Javier Del Ser +1
In the era of sustainable smart agriculture, a massive amount of agricultural news text is being posted on the Internet, in which massive agricultural knowledge has been accumulate…
On the Connection between Concept Drift and Uncertainty in Industrial Artificial Intelligence
Jesus L. Lobo, Ibai Laña, Eneko Osaba +1
AI-based digital twins are at the leading edge of the Industry 4.0 revolution, which are technologically empowered by the Internet of Things and real-time data analysis. Informatio…
Multiobjective Evolutionary Pruning of Deep Neural Networks with Transfer Learning for improving their Performance and Robustness
Javier Poyatos, Daniel Molina, Aitor Martínez +2
Evolutionary Computation algorithms have been used to solve optimization problems in relation with architectural, hyper-parameter or training configuration, forging the field known…
Region-Based Evidential Deep Learning to Quantify Uncertainty and Improve Robustness of Brain Tumor Segmentation
Hao Li, Yang Nan, Javier Del Ser +1
Despite recent advances in the accuracy of brain tumor segmentation, the results still suffer from low reliability and robustness. Uncertainty estimation is an efficient solution t…
Deep learning for understanding multilabel imbalanced Chest X-ray datasets
Helena Liz, Javier Huertas-Tato, Manuel Sánchez-Montañés +2
Over the last few years, convolutional neural networks (CNNs) have dominated the field of computer vision thanks to their ability to extract features and their outstanding performa…
Large-Kernel Attention for 3D Medical Image Segmentation
Hao Li, Yang Nan, Javier Del Ser +1
Automatic segmentation of multiple organs and tumors from 3D medical images such as magnetic resonance imaging (MRI) and computed tomography (CT) scans using deep learning methods…
Capabilities, Limitations and Challenges of Style Transfer with CycleGANs: A Study on Automatic Ring Design Generation
Tomas Cabezon Pedroso, Javier Del Ser, Natalia Diaz-Rodrıguez
Rendering programs have changed the design process completely as they permit to see how the products will look before they are fabricated. However, the rendering process is complic…
Analysis, Characterization, Prediction and Attribution of Extreme Atmospheric Events with Machine Learning: a Review
Sancho Salcedo-Sanz, Jorge Pérez-Aracil, Guido Ascenso +9
Atmospheric Extreme Events (EEs) cause severe damages to human societies and ecosystems. The frequency and intensity of EEs and other associated events are increasing in the curren…
An Evaluation Study of Intrinsic Motivation Techniques applied to Reinforcement Learning over Hard Exploration Environments
Alain Andres, Esther Villar-Rodriguez, Javier Del Ser
In the last few years, the research activity around reinforcement learning tasks formulated over environments with sparse rewards has been especially notable. Among the numerous ap…
Explainable COVID-19 Infections Identification and Delineation Using Calibrated Pseudo Labels
Ming Li, Yingying Fang, Zeyu Tang +5
The upheaval brought by the arrival of the COVID-19 pandemic has continued to bring fresh challenges over the past two years. During this COVID-19 pandemic, there has been a need f…
A Review of Deep Learning-based Approaches for Deepfake Content Detection
Leandro A. Passos, Danilo Jodas, Kelton A. P. da Costa +5
Recent advancements in deep learning generative models have raised concerns as they can create highly convincing counterfeit images and videos. This poses a threat to people's inte…
Multimodal Audio-Visual Information Fusion using Canonical-Correlated Graph Neural Network for Energy-Efficient Speech Enhancement
Leandro Aparecido Passos, João Paulo Papa, Javier Del Ser +2
This paper proposes a novel multimodal self-supervised architecture for energy-efficient audio-visual (AV) speech enhancement that integrates Graph Neural Networks with canonical c…