Search results for "konenäkö"

showing 10 items of 27 documents

Benchmark database for fine-grained image classification of benthic macroinvertebrates

2018

Managing the water quality of freshwaters is a crucial task worldwide. One of the most used methods to biomonitor water quality is to sample benthic macroinvertebrate communities, in particular to examine the presence and proportion of certain species. This paper presents a benchmark database for automatic visual classification methods to evaluate their ability for distinguishing visually similar categories of aquatic macroinvertebrate taxa. We make publicly available a new database, containing 64 types of freshwater macroinvertebrates, ranging in number of images per category from 7 to 577. The database is divided into three datasets, varying in number of categories (64, 29, and 9 categori…

0106 biological sciencesComputer scienceta1172Sample (statistics)monitorointi02 engineering and technologyneuroverkot01 natural sciencesConvolutional neural network0202 electrical engineering electronic engineering information engineeringkonenäköfine-grained classification14. Life underwaterFine-grained classificationInvertebrateta113ta112Contextual image classificationbusiness.industry010604 marine biology & hydrobiologyDeep learningConvolutional Neural NetworksBenchmark databasedeep learningPattern recognitionDeep learningselkärangattomatvedenlaatu6. Clean waterkoneoppiminenBenthic zoneBenthic macroinvertebratesbiomonitoringSignal ProcessingBiomonitoringta1181lajinmääritys020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligenceWater qualitybusinessbenthic macroinvertebrates
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BRIMA : Low-Overhead Browser-Only Image Annotation Tool

2021

Image annotation and large annotated datasets are crucial parts within the Computer Vision and Artificial Intelligence fields. At the same time, it is well-known and acknowledged by the research community that the image annotation process is challenging, time-consuming and hard to scale. Therefore, the researchers and practitioners are always seeking ways to perform the annotations easier, faster, and at higher quality. Even though several widely used tools exist and the tools’ landscape evolved considerably, most of the tools still require intricate technical setups and high levels of technical savviness from its operators and crowdsource contributors.In order to address such challenges, w…

COCOhahmontunnistus (tietotekniikka)selaimetjoukkoistaminenimage dataset generationcrowdsource annotationannotointiannotation toolkonenäköimage annotationkuvat
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Automatic image-based identification and biomass estimation of invertebrates

2020

1. Understanding how biological communities respond to environmental changes is a key challenge in ecology and ecosystem management. The apparent decline of insect populations necessitates more biomonitoring but the time-consuming sorting and expert-based identification of taxa pose strong limitations on how many insect samples can be processed. In turn, this affects the scale of efforts to map and monitor invertebrate diversity altogether. Given recent advances in computer vision, we propose to enhance the standard human expert-based identification approach involving manual sorting and identification with an automatic image-based technology. 2. We describe a robot-enabled image-based ident…

FOS: Computer and information sciences0106 biological sciencesclassification (action)Computer Science - Machine Learninghahmontunnistus (tietotekniikka)Computer scienceImage qualityComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern Recognitionclassificationsmodelling (creation related to information)neuroverkot01 natural sciencesConvolutional neural networkcomputer visionMachine Learning (cs.LG)remote sensingAbundance (ecology)Statistics - Machine Learningkonenäköinsectstunnistaminenbiodiversitysystematiikka (biologia)Ecological ModelingSortingselkärangattomatneural networksmuutosjohtaminenautomated pattern recognitionIdentification (information)machine learningkoneoppiminenclassificationEcosystem managementhämähäkitrecognitionmallintaminenneural networks (information technology)Machine Learning (stat.ML)010603 evolutionary biologyspidersidentifiointilajitsystematicsluokituksetEcology Evolution Behavior and Systematicsluokitus (toiminta)tarkkuusbusiness.industry010604 marine biology & hydrobiologyDeep learningPattern recognitiontypes and speciesidentification (recognition)15. Life on land113 Computer and information sciencesecosystems (ecology)invertebratesbiodiversiteettiekosysteemit (ekologia)hyönteisetidentificationprecisionkaukokartoitusArtificial intelligencechange management (leadership)businessScale (map)
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One-Pixel Attack Deceives Computer-Assisted Diagnosis of Cancer

2020

Computer vision and machine learning can be used to automate various tasks in cancer diagnostic and detection. If an attacker can manipulate the automated processing, the results can be devastating and in the worst case lead to wrong diagnosis and treatment. In this research, the goal is to demonstrate the use of one-pixel attacks in a real-life scenario with a real pathology dataset, TUPAC16, which consists of digitized whole-slide images. We attack against the IBM CODAIT's MAX breast cancer detector using adversarial images. These adversarial examples are found using differential evolution to perform the one-pixel modification to the images in the dataset. The results indicate that a mino…

FOS: Computer and information sciencesComputer Science - Machine LearningComputer Science - Cryptography and SecurityComputer scienceComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMachine Learning (cs.LG)Medical imagingComputer visionkonenäköIBMkyberturvallisuusPixelbusiness.industryPerspective (graphical)diagnostiikkakoneoppiminenDifferential evolutionWhole slide imageReversingsyöpätauditArtificial intelligencebusinessCryptography and Security (cs.CR)verkkohyökkäykset
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Computer Vision on X-ray Data in Industrial Production and Security Applications: A Comprehensive Survey

2023

X-ray imaging technology has been used for decades in clinical tasks to reveal the internal condition of different organs, and in recent years, it has become more common in other areas such as industry, security, and geography. The recent development of computer vision and machine learning techniques has also made it easier to automatically process X-ray images and several machine learning-based object (anomaly) detection, classification, and segmentation methods have been recently employed in X-ray image analysis. Due to the high potential of deep learning in related image processing applications, it has been used in most of the studies. This survey reviews the recent research on using com…

FOS: Computer and information sciencesGeneral Computer ScienceComputer Vision and Pattern Recognition (cs.CV)security applicationsröntgensäteilyComputer Science - Computer Vision and Pattern RecognitionGeneral Engineeringdeep learningsyväoppiminencomputer visionX-rayindustrial applicationskonenäköGeneral Materials ScienceElectrical and Electronic Engineering
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Fluid flow simulations meet high-speed video : Computer vision comparison of droplet dynamics

2018

Hypothesis While multiphase flows, particularly droplet dynamics, are ordinary in nature as well as in industrial processes, their mathematical and computational modelling continue to pose challenging research tasks - patent approaches for tackling them are yet to be found. The lack of analytical flow field solutions for non-trivial droplet dynamics hinders validation of computer simulations and, hence, their application in research problems. High-speed videos and computer vision algorithms can provide a viable approach to validate simulations directly against experiments. Experiments Droplets of water (or glycerol-water mixtures) impacting on both hydrophobic and superhydrophobic surfaces …

Physics::Fluid Dynamicsvideokuvausexperimentalhigh-speed videokokeet (tutkimustoiminta)droplethydrodynamiikkakonenäkösimulointihydrophobicLattice Boltzmannpisarat
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Accuracy of a computer vision system for estimating biomechanical measures of body function in axial spondyloarthropathy patients and healthy subjects

2023

Objective Advances in computer vision make it possible to combine low-cost cameras with algorithms, enabling biomechanical measures of body function and rehabilitation programs to be performed anywhere. We evaluated a computer vision system's accuracy and concurrent validity for estimating clinically relevant biomechanical measures. Design Cross-sectional study. Setting Laboratory. Participants Thirty-one healthy participants and 31 patients with axial spondyloarthropathy. Intervention A series of clinical functional tests (including the gold standard Bath Ankylosing Spondylitis Metrology Index tests). Each test was performed twice: the first performance was recorded with a camera, and a co…

Rehabilitationetäseurantaclinical testPhysical Therapy Sports Therapy and Rehabilitationkonenäkötekoälyartificial intelligencetelerehabilitationphysiotherapyremote monitoringcomputer visionfysioterapia
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Regressiomenetelmiä viljapellon biomassan estimointiin ortokuvista ja digitaalisesta korkeusmallista

2012

Tutkielmassa esitellään käyttötarkoitus biomassan estimoinnille ja vertaillaan kolmea regressiomenetelmää, lineaarista regressiota, k:n lähimmän naapurin menetelmää sekä tukivektoriregressiota. Tutkielmassa esitellään myös aineisto ja aineistoon suoritetut muunnokset.

biomassatukivektoriregressiolineaarinen regressiok-NNkonenäköestimointimenetelmät
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Ethical issues in topical computer vision applications

2017

Computer vision is a research area that contains multiple methods to approach numerous visual problems. In the past decade, it has been rapidly evolving with the introduction of many new technologies and applications that utilize different computer vision techniques. The purpose of this study is to identify the ethical issues that concern recent trending computer vision applications and their tasks. This was done by conducting an integrative literature review and synthesizing various studies that have been conducted on the different applications of computer vision and their ethical issues. The result was a synthesized framework of different ethics themes that relate to the different areas o…

computer ethicsKirjallisuuskatsaustieto- ja viestintätekniikkakonenäköetiikkaethicscomputer visiontieto- ja viestintärikokset
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Encryption and Generation of Images for Privacy-Preserving Machine Learning in Smart Manufacturing

2023

Current advances in machine (deep) learning and the exponential growth of data collected by and shared between smart manufacturing processes give a unique opportunity to get extra value from that data. The use of public machine learning services actualizes the issue of data privacy. Ordinary encryption protects the data but could make it useless for the machine learning objectives. Therefore, “privacy of data vs. value from data” is the major dilemma within the privacy preserving machine learning activity. Special encryption techniques or synthetic data generation are being in focus to address the issue. In this paper, we discuss a complex hybrid protection algorithm, which assumes sequenti…

data privacyIndustry 4.0anonymizationimage processingtietosuojakoneoppiminensalausautoencoderssyntetic data generationGeneral Earth and Planetary SciencesvalmistustekniikkakonenäköteollisuusanonymiteettiGeneral Environmental ScienceProcedia Computer Science
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