Search results for " artificial intelligence"

showing 10 items of 1992 documents

Automated detection of microaneurysms using robust blob descriptors

2013

International audience; Microaneurysms (MAs) are among the first signs of diabetic retinopathy (DR) that can be seen as round dark-red structures in digital color fundus photographs of retina. In recent years, automated computer-aided detection and diagnosis (CAD) of MAs has attracted many researchers due to its low-cost and versatile nature. In this paper, the MA detection problem is modeled as finding interest points from a given image and several interest point descriptors are introduced and integrated with machine learning techniques to detect MAs. The proposed approach starts by applying a novel fundus image contrast enhancement technique using Singular Value Decomposition (SVD) of fun…

Computer scienceSVMComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyFundus (eye)[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicine[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0202 electrical engineering electronic engineering information engineeringmedicineComputer visionRetinaRadon transformbusiness.industrySURFHessian[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Diabetic retinopathymedicine.diseaseMicroaneurysmSupport vector machinemedicine.anatomical_structureComputer-aided diagnosis020201 artificial intelligence & image processingArtificial intelligencebusinessSVDRetinopathy
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An Automatic HEp-2 Specimen Analysis System Based on an Active Contours Model and an SVM Classification

2019

The antinuclear antibody (ANA) test is widely used for screening, diagnosing, and monitoring of autoimmune diseases. The most common methods to determine ANA are indirect immunofluorescence (IIF), performed by human epithelial type 2 (HEp-2) cells, as substrate antigen. The evaluation of ANA consist an analysis of fluorescence intensity and staining patterns. This paper presents a complete and fully automatic system able to characterize IIF images. The fluorescence intensity classification was obtained by performing an image preprocessing phase and implementing a Support Vector Machines (SVM) classifier. The cells identification problem has been addressed by developing a flexible segmentati…

Computer scienceSVMKNN02 engineering and technologylcsh:TechnologyIIF imageHough transformlaw.inventionlcsh:Chemistry03 medical and health scienceslawClassifier (linguistics)0202 electrical engineering electronic engineering information engineeringPreprocessorGeneral Materials ScienceSegmentationcell segmentationlcsh:QH301-705.5InstrumentationIIF images030304 developmental biologyFluid Flow and Transfer Processes0303 health sciencesIndirect immunofluorescencelcsh:Tbusiness.industryProcess Chemistry and TechnologyGeneral EngineeringPattern recognitionSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)ROC curvelcsh:QC1-999Computer Science ApplicationsSupport vector machineParameter identification problemFluorescence intensityHough transformlcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040020201 artificial intelligence & image processingArtificial intelligencelcsh:Engineering (General). Civil engineering (General)businesslcsh:Physicsactive contours modelApplied Sciences
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Incomplete 3D motion trajectory segmentation and 2D-to-3D label transfer for dynamic scene analysis

2017

International audience; The knowledge of the static scene parts and the moving objects in a dynamic scene plays a vital role for scene modelling, understanding, and landmark-based robot navigation. The key information for these tasks lies on semantic labels of the scene parts and the motion trajectories of the dynamic objects. In this work, we propose a method that segments the 3D feature trajectories based on their motion behaviours, and assigns them semantic labels using 2D-to-3D label transfer. These feature trajectories are constructed by using the proposed trajectory recovery algorithm which takes the loss of feature tracking into account. We introduce a complete framework for static-m…

Computer scienceScene UnderstandingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Motion (physics)[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0502 economics and business0202 electrical engineering electronic engineering information engineering[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]Computer visionSegmentationMotion Segmentation050210 logistics & transportationbusiness.industry[INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO][ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO]05 social sciences3D reconstruction[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]2D to 3D conversionFeature (computer vision)TrajectoryKey (cryptography)Robot020201 artificial intelligence & image processingArtificial intelligence3D Reconstructionbusiness2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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Overview of the Second BUCC Shared Task: Spotting Parallel Sentences in Comparable Corpora

2017

This paper presents the BUCC 2017 shared task on parallel sentence extraction from comparable corpora. It recalls the design of the datasets, presents their final construction and statistics and the methods used to evaluate system results. 13 runs were submitted to the shared task by 4 teams, covering three of the four proposed language pairs: French-English (7 runs), German-English (3 runs), and Chinese-English (3 runs). The best F-scores as measured against the gold standard were 0.84 (German-English), 0.80 (French-English), and 0.43 (Chinese-English). Because of the design of the dataset, in which not all gold parallel sentence pairs are known, these are only minimum values. We examined …

Computer scienceSentence extractionbusiness.industrySpeech recognition020206 networking & telecommunications02 engineering and technologyGold standard (test)Spottingcomputer.software_genreTask (project management)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerNatural language processingSentenceProceedings of the 10th Workshop on Building and Using Comparable Corpora
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Classification of Melanoma Lesions Using Sparse Coded Features and Random Forests

2016

International audience; Malignant melanoma is the most dangerous type of skin cancer, yet it is the most treatable kind of cancer, conditioned by its early diagnosis which is a challenging task for clinicians and dermatologists. In this regard, CAD systems based on machine learning and image processing techniques are developed to differentiate melanoma lesions from benign and dysplastic nevi using dermoscopic images. Generally, these frameworks are composed of sequential processes: pre-processing, segmentation, and classification. This architecture faces mainly two challenges: (i) each process is complex with the need to tune a set of parameters, and is specific to a given dataset; (ii) the…

Computer scienceSparse codingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-invariant feature transformImage processingDermoscopy02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineHistogram0202 electrical engineering electronic engineering information engineeringmedicineComputer visionSegmentationMelanoma[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingbusiness.industryMelanomaCancerPattern recognitionImage segmentationSparse approximationRandom forestsmedicine.diseaseClassificationRandom forest020201 artificial intelligence & image processingArtificial intelligenceSkin cancerNeural codingbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Morphological Analysis Combined with a Machine Learning Approach to Detect Utrasound Median Sagittal Sections for the Nuchal Translucency Measurement

2017

The screening of chromosomal defects, as trisomy 13, 18 and 21, can be obtained by the measurement of the nuchal translucency thickness scanning during the end of the first trimester of pregnancy. This contribution proposes an automatic methodology to detect mid-sagittal sections to identify the correct measurement of nuchal translucency. Wavelet analysis and neural network classifiers are the main strategies of the proposed methodology to detect the frontal components of the skull and the choroid plexus with the support of radial symmetry analysis. Real clinical ultrasound images were adopted to measure the performance and the robustness of the methodology, thus it can be highlighted an er…

Computer scienceSpeech recognition02 engineering and technologyWavelet analysi03 medical and health sciences0302 clinical medicineWaveletMid-sagittal section Neural network Nuchal translucency Symmetry transform Wavelet analysis.Nuchal translucencyRobustness (computer science)Nuchal Translucency Measurement0202 electrical engineering electronic engineering information engineeringmedicineMid-sagittal sectionSettore INF/01 - InformaticaArtificial neural networkbusiness.industrySymmetry transformPattern recognitionmedicine.diseaseNeural networkSagittal planemedicine.anatomical_structureNuchal translucencyMorphological analysis020201 artificial intelligence & image processingArtificial intelligenceTrisomybusiness030217 neurology & neurosurgery
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Depression Assessment by Fusing High and Low Level Features from Audio, Video, and Text

2016

International audience; Depression is a major cause of disability world-wide. The present paper reports on the results of our participation to the depression sub-challenge of the sixth Audio/Visual Emotion Challenge (AVEC 2016), which was designed to compare feature modalities ( audio, visual, interview transcript-based) in gender-based and gender-independent modes using a variety of classification algorithms. In our approach, both high and low level features were assessed in each modality. Audio features were extracted from the low-level descriptors provided by the challenge organizers. Several visual features were extracted and assessed including dynamic characteristics of facial elements…

Computer scienceSpeech recognitionPosterior probabilitymultimodal fusionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processing02 engineering and technology[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][SPI]Engineering Sciences [physics]AVEC 2016Histogram0202 electrical engineering electronic engineering information engineeringFeature (machine learning)[ SPI ] Engineering Sciences [physics]Affective computingaffective computing[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]speech processing[SPI.ACOU]Engineering Sciences [physics]/Acoustics [physics.class-ph]Modality (human–computer interaction)[ SPI.ACOU ] Engineering Sciences [physics]/Acoustics [physics.class-ph]pattern recognition020206 networking & telecommunicationsSpeech processingimage processingStatistical classificationdepression assessment13. Climate actionPattern recognition (psychology)020201 artificial intelligence & image processing
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Uncalibrated Reconstruction: An Adaptation to Structured Light Vision

2003

Abstract Euclidean reconstruction from two uncalibrated stereoscopic views is achievable from the knowledge of geometrical constraints about the environment. Unfortunately, these constraints may be quite difficult to obtain. In this paper, we propose an approach based on structured lighting, which has the advantage of providing geometrical constraints independent of the scene geometry. Moreover, the use of structured light provides a unique solution to the tricky correspondence problem present in stereovision. The projection matrices are first computed by using a canonical representation, and a projective reconstruction is performed. Then, several constraints are generated from the image an…

Computer scienceStereoscopy02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]01 natural scienceslaw.invention010309 optics[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Projection (mathematics)Artificial Intelligencelaw0103 physical sciencesEuclidean geometry0202 electrical engineering electronic engineering information engineeringComputer visionCorrespondence problemComputingMilieux_MISCELLANEOUSbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Mobile robot navigationSignal Processing020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionAffine transformationArtificial intelligencebusinessSoftwareStructured light
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Indoor Space Classification Using Cascaded LSTM

2020

Author's accepted manuscript. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Indoor space classification is an important part of localization that helps in precise location extraction, which has been extensively utilized in industrial and domestic domain. There are various approaches that employ Bluetooth Low Energy (BLE), Wi-Fi, magnetic field, object detecti…

Computer scienceUltra-wideband020302 automobile design & engineering02 engineering and technologySpace (commercial competition)computer.software_genreObject detectionlaw.inventionDomain (software engineering)Bluetooth0203 mechanical engineeringlaw0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingData miningcomputerVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550
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Tracking Hands in Interaction with Objects: A Review

2017

Markerless vision-based 3D hand motion tracking is a key and popular component for interaction studies in many domains such as virtual reality and natural human-computer interfaces. While this research field has been well studied in the last decades, most approaches have considered the human hand in isolation and not in action or in interaction with the environment or the other articulated human body parts. Employing contextual information about the surrounding environment (e.g. the shape, the texture, and the posture of the object in the hand) can remarkably constrain the tracking problem. The goal of this survey is to develop an up-to-date taxonomy of existing vision-based hand tracking m…

Computer science[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineering02 engineering and technologyVirtual reality[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Object (philosophy)Field (computer science)Domain (software engineering)Action (philosophy)Human–computer interactionTaxonomy (general)Component (UML)[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingPoseComputingMilieux_MISCELLANEOUS
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