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Auflistung Nach Schlagwort "Image enhancement"

Anzeige der Dokumente 1-13 von 13

    • Assessing Durum Wheat Yield through Sentinel-2 Imagery: A Machine Learning Approach 

      Bebie M., Cavalaris C., Kyparissis A. (2022)
      Two modeling approaches for the estimation of durum wheat yield based on Sentinel-2 data are presented for 66 fields across three growing periods. In the first approach, a previously developed multiple linear regression ...

    • Bismuth oxyhalide based photo-enhanced triboelectric nanogenerators 

      Yu Z., Yang H., Soin N., Chen L., Black N., Xu K., Sharma P.K., Tsonos C., Kumar A., Luo J. (2021)
      Utilizing wide absorption characteristics of a narrow bandgap (~1.8 eV) semiconductor, we report on Bismuth Oxyiodide (BiOI) based photo-enhanced triboelectric nanogenerator (TENG). The potentiostatic deposition of ...

    • Convolutional neural networks for pose recognition in binary omni-directional images 

      Georgakopoulos S.V., Kottari K., Delibasis K., Plagianakos V.P., Maglogiannis I. (2016)
      In this work, we present a methodology for pose classification of silhouettes using convolutional neural networks. The training set consists exclusively from the synthetic images that are generated from three-dimensional ...

    • Enhanced CNN-Based gaze estimation on wireless capsule endoscopy images 

      Gatoula P., Dimas G., Iakovidis D.K., Koulaouzidis A. (2021)
      Wireless capsule endoscopy (WCE) is a modality used for the non-invasive examination of the gastrointestinal (GI) tract. Physicians diagnose pathologies in images derived from Capsule Endoscopy (CE) using specific gaze ...

    • H-V shadow detection based on electromagnetism-like optimization 

      Koutsiou D.-C.C., Savelonas M., Iakovidis D.K. (2021)
      Shadow detection is useful in a variety of image analysis applications, as it can improve scene understanding. Most of the recent shadow detection approaches use near-infrared (NIR) cameras and deep learning to provide ...

    • Improved Face Detector on Fisheye Images via Spherical-Domain Attention 

      Miao J., Liu Y., Liu J., Argyriou A., Xu Z., Han Y. (2021)
      As one type of omnidirectional projection, fisheye images have been widely used in automatic driving and visual surveillance. However, they cannot be processed well by the traditional algorithms designed for the planar ...

    • Improving the performance of convolutional neural network for skin image classification using the response of image analysis filters 

      Georgakopoulos S.V., Kottari K., Delibasis K., Plagianakos V.P., Maglogiannis I. (2019)
      In this work, we focus in the analysis of dermoscopy images using convolutional neural networks (CNNs). More specifically, we investigate the value of augmenting CNN inputs with the response of mid-level computer vision ...

    • Information content in nuclear medicine imaging 

      Michail C.M., Agavanakis K.N., Karpetas G.E., Kalyvas N.I., Valais I.G., Kandarakis I.S., Panayiotakis G.S., Fountos G.P. (2019)
      The aim of the present study was to investigate the information content of positron emission tomography (PET) images. We used the GATE Monte Carlo package (GEANT4 application for tomographic emission) and reconstructed ...

    • Investigating cross-dataset abnormality detection in endoscopy with a weakly-supervised multiscale convolutional neural network 

      Diamantis D., Iakovidis D.K., Koulaouzidis A. (2018)
      The detection of abnormalities in endoscopic video frames can contribute in the early and more accurate detection of pathologic conditions. In this paper we present a novel Convolutional Neural Network (CNN) architecture ...

    • Latent twitter image information for social analytics 

      Razis G., Theofilou G., Anagnostopoulos I. (2021)
      The appearance of images in social messages is continuously increasing, along with user engagement with that type of content. Analysis of social images can provide valuable latent information, often not present in the ...

    • An open web services - Based framework for data mining of biomedical image data 

      Doukas, C.; Maglogiannis, I.; Chatziioannou, A. (2009)
      Mining of biomedical image data is a complex procedure that requires several processing phases, such as data acquisition, preprocessing (e.g., image enhancement, color processing), feature extraction and classification. ...

    • Pose recognition using convolutional neural networks on omni-directional images 

      Georgakopoulos S.V., Kottari K., Delibasis K., Plagianakos V.P., Maglogiannis I. (2018)
      Convolutional neural networks (CNNs) are used frequently in several computer vision applications. In this work, we present a methodology for pose classification of binary human silhouettes using CNNs, enhanced with image ...

    • Roadmap on signal processing for next generation measurement systems 

      Iakovidis D.K., Ooi M., Kuang Y.C., Demidenko S., Shestakov A., Sinitsin V., Henry M., Sciacchitano A., Discetti S., Donati S., Norgia M., Menychtas A., Maglogiannis I., Wriessnegger S.C., Chacon L.A.B., Dimas G., Filos D., Aletras A.H., Töger J., Dong F., Ren S., Uhl A., Paziewski J., Geng J., Fioranelli F., Narayanan R.M., Fernandez C., Stiller C., Malamousi K., Kamnis S., Delibasis K., Wang D., Zhang J., Gao R.X. (2022)
      Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative ...