Search results for "classification"

showing 4 items of 4 documents

Tree Species Classification of Drone Hyperspectral and RGB Imagery with Deep Learning Convolutional Neural Networks

2020

Interest in drone solutions in forestry applications is growing. Using drones, datasets can be captured flexibly and at high spatial and temporal resolutions when needed. In forestry applications, fundamental tasks include the detection of individual trees, tree species classification, biomass estimation, etc. Deep neural networks (DNN) have shown superior results when comparing with conventional machine learning methods such as multi-layer perceptron (MLP) in cases of huge input data. The objective of this research is to investigate 3D convolutional neural networks (3D-CNN) to classify three major tree species in a boreal forest: pine, spruce, and birch. The proposed 3D-CNN models were emp…

010504 meteorology & atmospheric sciencesComputer sciencehyperspectral image classificationScience0211 other engineering and technologiesgeoinformatics02 engineering and technologyneuroverkot01 natural sciencesConvolutional neural networkpuulajitPARAMETERSSet (abstract data type)LIDARFORESTSClassifier (linguistics)021101 geological & geomatics engineering0105 earth and related environmental sciencesbusiness.industryDeep learningspektrikuvausQHyperspectral imagingdeep learningPattern recognition15. Life on landmiehittämättömät ilma-aluksetPerceptron113 Computer and information sciencesClass (biology)drone imagery3d convolutional neural networksmetsänarviointiMACHINEkoneoppiminentree species classification3D convolutional neural networksGeneral Earth and Planetary SciencesRGB color modelArtificial intelligencekaukokartoitusbusinesshyperspectral image classificationRemote Sensing
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Classification of Sequences with Deep Artificial Neural Networks: Representation and Architectural Issues

2021

DNA sequences are the basic data type that is processed to perform a generic study of biological data analysis. One key component of the biological analysis is represented by sequence classification, a methodology that is widely used to analyze sequential data of different nature. However, its application to DNA sequences requires a proper representation of such sequences, which is still an open research problem. Machine Learning (ML) methodologies have given a fundamental contribution to the solution of the problem. Among them, recently, also Deep Neural Network (DNN) models have shown strongly encouraging results. In this chapter, we deal with specific classification problems related to t…

SequenceBiological dataSequence classificationSettore INF/01 - InformaticaArtificial neural networkProcess (engineering)Computer sciencebusiness.industryDeep learningBacteria classificationSequence classificationBacteria classificationNucleosome identificationDeep neural networkMachine learningcomputer.software_genreData typeNucleosome identificationComponent (UML)Artificial intelligenceMetagenomicsRepresentation (mathematics)businesscomputer
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Geometric représentations of the braid groups

2010

We show that the morphisms from the braid group with n strands in the mapping class group of a surface with a possible non empty boundary, assuming that its genus is smaller or equal to n/2 are either cyclic morphisms (their images are cyclic groups), or transvections of monodromy morphisms (up to multiplication by an element in the centralizer of the image, the image of a standard generator of the braid group is a Dehn twist, and the images of two consecutive standard generators are two Dehn twists along two curves intersecting in one point). As a corollary, we determine the endomorphisms, the injective endomorphisms, the automorphisms and the outer automorphism group of the following grou…

[ MATH ] Mathematics [math]rigidité[ MATH.MATH-GR ] Mathematics [math]/Group Theory [math.GR]morphisme de monodromieification de Nielsen Thurstonbraid groupGroup Theory (math.GR)[MATH] Mathematics [math]groupe de difféotopies[MATH.MATH-GR]Mathematics [math]/Group Theory [math.GR]monodromieFOS: Mathematicssurface[MATH]Mathematics [math]représentation géométriquetransvectionmonodromymapping class groupMathematics::Geometric TopologyrigidityNielsen-Thurstongroupe de tressesAMS Subject Classification: Primary 20F38 57M07. Secondary 57M99 20F36 20E36 57M05.mapping groupMathematics - Group Theorygroupe de diffétopies
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Editorial for the Special Issue “Frontiers in Spectral Imaging and 3D Technologies for Geospatial Solutions”

2019

This Special Issue hosts papers on the integrated use of spectral imaging and 3D technologies in remote sensing, including novel sensors, evolving machine learning technologies for data analysis, and the utilization of these technologies in a variety of geospatial applications. The presented results showed improved results when multimodal data was used in object analysis.

medicine.medical_specialtyGeospatial analysisComputer sciencehyperspectral imagingSciencecomputer.software_genrehyperspectral imaging; point cloud; sensor integration; data fusion; machine learning; deep learning; classification; estimation; semantic segmentation; object detection; point cloud filteringmedicine3D-mallinnussensor integrationpoint cloud filteringdata fusionestimationbusiness.industryDeep learningspektrikuvausQHyperspectral imagingdeep learningobject detectionSensor fusionObject (computer science)Data scienceObject detectionsemantic segmentationSpectral imagingVariety (cybernetics)classificationpoint cloud filteringsegmentointikoneoppiminenmachine learningclassificationGeneral Earth and Planetary SciencesArtificial intelligencekaukokartoitusbusinesscomputerpoint cloudRemote Sensing
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