Search results for " machine"
showing 10 items of 1317 documents
Processing of 3D Models for Networking of CH in Geomatics
2020
In recent times the possibility of reconstruction of complex 3D Cultural Heritage (CH) environments has opened new scenarios for touristic and scientific aims. The different needs for networking or conservation purposes of CH lead to study proper structuring of 3D models. In light of this, a scientific approach has been developed in order to test the networking capabilities, comparing different loading configurations of 3D environments with multiple combinations of 3D models inside them, considering different solutions. This experimentation has been based on WebGL-HTML5 technologies and allowed to discover the true balance between performances of proposed system, the quality of visualizatio…
Learning automata based energy-efficient AI hardware design for IoT applications
2020
Energy efficiency continues to be the core design challenge for artificial intelligence (AI) hardware designers. In this paper, we propose a new AI hardware architecture targeting Internet of Things applications. The architecture is founded on the principle of learning automata, defined using propositional logic. The logic-based underpinning enables low-energy footprints as well as high learning accuracy during training and inference, which are crucial requirements for efficient AI with long operating life. We present the first insights into this new architecture in the form of a custom-designed integrated circuit for pervasive applications. Fundamental to this circuit is systematic encodin…
Distributed channel prediction for multi-agent systems
2017
Los sistemas multiagente (MAS) se comunican a través de una red inalámbrica para coordinar sus acciones e informar sobre el estado de su misión. La conectividad y el rendimiento del sistema pueden mejorarse mediante la predicción de la ganancia del canal. Presentamos un esquema basado en regresión de procesos gaussianos (GPR) distribuidos para predecir el canal inalámbrico en términos de la potencia recibida en el MAS. El esquema combina una máquina de comité bayesiano con un esquema de consenso medio, distribuyendo así no sólo la memoria sino también la carga computacional y de comunicación. A través de simulaciones de Monte Carlo, demostramos el rendimiento del GPR propuesto. RACHEL TEC20…
Основы радиотехники, часть 2
1921
Apprentissage automatique de réseaux d'interaction à partir de données de séquences de nouvelle génération
2022
Climate change and other human-induced processes are modifying ecosystems, globally, at an ever increasing rate. Microbial communities play an important role in the functioning ecosystems, maintaining their diversity and services. These communities are shaped by the different abiotic environmental effects to which they are subjected and the biotic interactions between all community members. The ANR Next-Generation Biomonitoring (NGB) project proposed to reconstruct interaction networks from abundance measures obtained sequencing environmental DNA (eDNA) and to use these networks to monitor ecosystem change. In this thesis, conducted as part of the NGB project, I evaluate the potential of tw…
Lung on a Chip Development from Off-Stoichiometry Thiol–Ene Polymer
2021
Institute of Solid-State Physics, University of Latvia as the Center of Excellence has received funding from the European Union’s Horizon 2020 Framework Programme H2020-WIDESPREAD-01-2016-2017-TeamingPhase2 under grant agreement No. 739508, project CAMART2. Finally, we would like to thank Biol. Kaspars Tars from Latvian Biomedical research and study center for giving us the opportunity to participate in this consortium and contribute to Latvian scientists’ effort in response to the COVID-19 pandemic.
Active learning strategies for the deduplication of electronic patient data using classification trees.
2012
Graphical abstractDisplay Omitted Highlights? Active learning for medical record linkage is used on a large data set. ? We compare a simple active learning strategy with a more sophisticated variant. ? The active learning method of Sarawagi and Bhamidipaty (2002) 6] is extended. ? We deliver insights into the variations of the results due to random sampling in the active learning strategies. IntroductionSupervised record linkage methods often require a clerical review to gain informative training data. Active learning means to actively prompt the user to label data with special characteristics in order to minimise the review costs. We conducted an empirical evaluation to investigate whether…
Remote sensing image segmentation by active queries
2012
Active learning deals with developing methods that select examples that may express data characteristics in a compact way. For remote sensing image segmentation, the selected samples are the most informative pixels in the image so that classifiers trained with reduced active datasets become faster and more robust. Strategies for intelligent sampling have been proposed with model-based heuristics aiming at the search of the most informative pixels to optimize model's performance. Unlike standard methods that concentrate on model optimization, here we propose a method inspired in the cluster assumption that holds in most of the remote sensing data. Starting from a complete hierarchical descri…
Discovering single classes in remote sensing images with active learning
2012
When dealing with supervised target detection, the acquisition of labeled samples is one of the most critical phases: the samples must be yet representative of the class of interest, but must also be found among a vast majority of non-target examples. Moreover, the efficiency of the search is also an issue, since the samples labeled as background are not used by target detectors such as the support vector data description (SVDD). In this work we propose a competitive and effective approach to identify the most relevant training samples for one-class classification based on the use of an active learning strategy. The SVDD classifier is first trained with insufficient target examples. It is t…
Improving active learning methods using spatial information
2011
Active learning process represents an interesting solution to the problem of training sample collection for the classification of remote sensing images. In this work, we propose a criterion based on the spatial information that can be used in combination with a spectral criterion in order to improve the selection of training samples. Experimental results obtained on a very high resolution image show the effectiveness of regularization in spatial domain and open challenging perspectives for terrain campaigns planning. © 2011 IEEE.