• Classification of Bulk Cargo Types Stored Openly at Ports Using CNN 

      Koirala, Madhu; Ellingsen, Pål Gunnar; Ådland, Roar Os (Chapter; Bokkapittel, 2023)
      In this paper, we present a novel concept of tracking cargoes at open ports using remote sensing images and convolution neural network (CNN) to classify various dry bulk commodities. The dataset used is prepared using Sentinel-2 atmospherically corrected (Sentinel-2 L2A) images covering 12 spectral bands. There are total 4995 labeled and geo-referenced images for four different cargoes-bauxite, ...
    • Classification of bulk cargo types stored openly at ports using CNN 

      Koirala, Madhu; Ellingsen, Pål Gunnar; Ådland, Roar Os (Chapter; Bokkapittel, 2023-10-20)
      In this paper, we present a novel concept of tracking cargoes at open ports using remote sensing images and convolution neural network (CNN) to classify various dry bulk commodities. The dataset used is prepared using Sentinel-2 atmospherically corrected (Sentinel-2 L2A) images covering 12 spectral bands. There are total 4995 labeled and geo-referenced images for four different cargoes-bauxite, coal, ...
    • Integrating Various Sensor Readings from MySignals into a Standalone Mobile Health App 

      Koirala, Madhu (Master thesis; Mastergradsoppgave, 2021-05-22)
      This project integrates various health parameters Temperature, Heart Rate, Pulse Rate, Blood Pressure, Respiration Rate, ECG, EMG, GSR, Spirometry values, Snore, Blood Sugar, Body Positions and Weight measured through wired and wireless sensors, into a standalone mobile health app. It shows Health Status of the user based on these parameters, and displays the values in different colors for normal ...