62 citations · 377 across the 29 of their papers we have counts for
13 papers · 1 filter
Speech Command Recognition in Computationally Constrained Environments with a Quadratic Self-organized Operational Layer
Mohammad Soltanian, Junaid Malik, Jenni Raitoharju +3
Automatic classification of speech commands has revolutionized human computer interactions in robotic applications. However, employed recognition models usually follow the methodol…
Graph Embedding with Data Uncertainty
Firas Laakom, Jenni Raitoharju, Nikolaos Passalis +2
spectral-based subspace learning is a common data preprocessing step in many machine learning pipelines. The main aim is to learn a meaningful low dimensional embedding of the data…
Collaborative Multi-Robot Systems for Search and Rescue: Coordination and Perception
Jorge Peña Queralta, Jussi Taipalmaa, Bilge Can Pullinen +6
Autonomous or teleoperated robots have been playing increasingly important roles in civil applications in recent years. Across the different civil domains where robots can support…
Monte Carlo Dropout Ensembles for Robust Illumination Estimation
Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis +2
Computational color constancy is a preprocessing step used in many camera systems. The main aim is to discount the effect of the illumination on the colors in the scene and restore…
AutoSOS: Towards Multi-UAV Systems Supporting Maritime Search and Rescue with Lightweight AI and Edge Computing
Jorge Peña Queralta, Jenni Raitoharju, Tuan Nguyen Gia +2
Rescue vessels are the main actors in maritime safety and rescue operations. At the same time, aerial drones bring a significant advantage into this scenario. This paper presents t…
Probabilistic Color Constancy
Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis +3
In this paper, we propose a novel unsupervised color constancy method, called Probabilistic Color Constancy (PCC). We define a framework for estimating the illumination of a scene…
Saliency-based Weighted Multi-label Linear Discriminant Analysis
Lei Xu, Jenni Raitoharju, Alexandros Iosifidis +1
In this paper, we propose a new variant of Linear Discriminant Analysis (LDA) to solve multi-label classification tasks. The proposed method is based on a probabilistic model for d…
Not all domains are equally complex: Adaptive Multi-Domain Learning
Ali Senhaji, Jenni Raitoharju, Moncef Gabbouj +1
Deep learning approaches are highly specialized and require training separate models for different tasks. Multi-domain learning looks at ways to learn a multitude of different task…
Ellipsoidal Subspace Support Vector Data Description
Fahad Sohrab, Jenni Raitoharju, Alexandros Iosifidis +1
In this paper, we propose a novel method for transforming data into a low-dimensional space optimized for one-class classification. The proposed method iteratively transforms data…
aColor: Mechatronics, Machine Learning, and Communications in an Unmanned Surface Vehicle
Jose Villa, Jussi Taipalmaa, Mikhail Gerasimenko +13
The aim of this work is to offer an overview of the research questions, solutions, and challenges faced by the project aColor ("Autonomous and Collaborative Offshore Robotics"). Th…
Boosting rare benthic macroinvertebrates taxa identification with one-class classification
Fahad Sohrab, Jenni Raitoharju
Insect monitoring is crucial for understanding the consequences of rapid ecological changes, but taxa identification currently requires tedious manual expert work and cannot be sca…
Incremental Fast Subclass Discriminant Analysis
Kateryna Chumachenko, Jenni Raitoharju, Moncef Gabbouj +1
This paper proposes an incremental solution to Fast Subclass Discriminant Analysis (fastSDA). We present an exact and an approximate linear solution, along with an approximate kern…
Automatic image-based identification and biomass estimation of invertebrates
Johanna Ärje, Claus Melvad, Mads Rosenhøj Jeppesen +8
Understanding how biological communities respond to environmental changes is a key challenge in ecology and ecosystem management. The apparent decline of insect populations necessi…