Blar i TKD - Institutt for informasjonsteknologi på emneord "VDP::Technology: 500::Information and communication technology: 550::Computer technology: 551"

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    • Design and Development of a Real-Time Monitoring System for Multiple Lead–Acid Batteries Based on Internet of Things 

      Rauniyar, Ashish; Irfan, Mohammad; Saputra, Oka Danil; Kim, Jin Woo; Lee, Ah Ra; Jang, Jae Min; Shin, Soo Young (Journal article; Peer reviewed, 2017)
      In this paper, real-time monitoring of multiple lead-acid batteries based on Internet of things is proposed and evaluated. Our proposed system monitors and stores parameters that provide an indication of the lead acid ...

    • Kvasir-SEG: A Segmented Polyp Dataset 

      Jha, Debesh; Pia H, Smedsrud; Riegler, Michael; Halvorsen, Pål; de Lange, Thomas; Johansen, Dag; Johansen, Håvard D. (Lecture Notes in Computer Science;Volume 11962, Conference object, 2019-12-24)
      Pixel-wise image segmentation is a highly demanding task in medical-image analysis. In practice, it is difficult to find annotated medical images with corresponding segmentation masks. In this paper, we present Kvasir-SEG: ...

    • Machine Learning-Based Analysis of Sperm Videos and Participant Data for Male Fertility Prediction 

      Hicks, Steven; Andersen, Jorunn Marie; Witczak, Oliwia; Lasantha Bandara Thambawita, Vajira; Halvorsen, Pål; Hammer, Hugo Lewi; Haugen, Trine B.; Riegler, Michael Alexander (Scientific Reports;9, Article number: 16770 (2019), Journal article; Peer reviewed, 2019-10-24)
      Methods for automatic analysis of clinical data are usually targeted towards a specific modality and do not make use of all relevant data available. In the field of male human reproduction, clinical and biological data are ...

    • ResUNet++: An Advanced Architecture for Medical Image Segmentation 

      Jha, Debesh; Smedsrud, Pia; Riegler, Michael; Johansen, Dag; de Lange, Thomas; Halvorsen, Pål; Johansen, Håvard D. (IEEE International Symposium on Multimedia; 2019 IEEE International Symposium on Multimedia (ISM), Conference object, 2020-01-16)
      Accurate computer-aided polyp detection and segmentation during colonoscopy examinations can help endoscopists resect abnormal tissue and thereby decrease chances of polyps growing into cancer. Towards developing a fully ...