201 citations · 919 across the 35 of their papers we have counts for
8 papers · 1 filter
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.…