Alberto Ortiz

Full Professor

Universitat de les Illes Balears

Spain

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About

Alberto Ortiz is a Full Professor at Universitat de les Illes Balears in Spain. His research areas encompass incremental learning methodologies, explainable deep learning architectures, and optimization techniques in multi-robot systems. He has published recent articles focusing on catastrophic forgetting in machine learning, district heating load forecasting, and robust LiDAR odometry, among other innovative topics in computer science and engineering.

Articles (15)

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2025

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2025

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2024

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2023

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2022

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2022

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2022

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2022

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2022

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2022

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2022

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2021

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2021

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2021

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2020

Collaborators (1)

Vincent Canals

University of the Balearic Islands

SPAIN

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Alberto Ortiz

Research Interests

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Articles (15)

Incremental Learning Methodologies for Addressing Catastrophic Forgetting: Analysis and Experimental Evaluation

Explainable district heating load forecasting by means of a reservoir computing deep learning architecture

SpeCluRC-NTL: Spearman’s distance-based clustering Reservoir Computing solution for NTL detection in smart grids

Multi-robot task allocation methods: A fuzzy optimization approach

MSC-VO: Exploiting Manhattan and Structural Constraints for Visual Odometry

Appearance-based loop closure detection combining lines and learned points for low-textured environments

MSC-VO: Exploiting Manhattan and Structural Constraints for Visual Odometry

A DCNN-based arbitrarily-oriented object detector with application to quality control and inspection

A DCNN-based arbitrarily-oriented object detector with application to quality control and inspection

LiODOM: Adaptive local mapping for robust LiDAR-only odometry

LiODOM: Adaptive local mapping for robust LiDAR-only odometry

MUSSOL: A Micro-Uas to Survey Ship Cargo hOLds

A Weakly-Supervised Semantic Segmentation Approach Based on the Centroid Loss: Application to Quality Control and Inspection

LiODOM: Adaptive Local Mapping for Robust LiDAR-Only Odometry

UWB-Based Self-Localization Strategies: A Novel ICP-Based Method and a Comparative Assessment for Noisy-Ranges-Prone Environments

Collaborators (1)

Vincent Canals

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