Search Results - "Matavulj, Predrag"

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  1. 1

    Manual and automatic quantification of airborne fungal spores during wheat harvest period by Simović, Isidora, Matavulj, Predrag, Šikoparija, Branko

    Published in Aerobiologia (01-06-2023)
    “…Due to the large diversity and quantity of fungal spores, such aerobiological studies are not so abundant and haven’t been done in Serbia so far. As the…”
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    Journal Article
  2. 2

    Explainable AI for unveiling deep learning pollen classification model based on fusion of scattered light patterns and fluorescence spectroscopy by Brdar, Sanja, Panić, Marko, Matavulj, Predrag, Stanković, Mira, Bartolić, Dragana, Šikoparija, Branko

    Published in Scientific reports (24-02-2023)
    “…Pollen monitoring have become data-intensive in recent years as real-time detectors are deployed to classify airborne pollen grains. Machine learning models…”
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    Journal Article
  3. 3

    Advanced CNN Architectures for Pollen Classification: Design and Comprehensive Evaluation by Matavulj, Predrag, Panić, Marko, Šikoparija, Branko, Tešendić, Danijela, Radovanović, Miloš, Brdar, Sanja

    Published in Applied artificial intelligence (31-12-2023)
    “…Allergenic pollen affects the quality of life for over 30% of the European population. Since the treatment efficacy is highly related to the actual exposure to…”
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    Journal Article
  4. 4

    Interseasonal transfer learning for crop mapping using Sentinel-1 data by Pandžić, Miloš, Pavlović, Dejan, Matavulj, Predrag, Brdar, Sanja, Marko, Oskar, Crnojević, Vladimir, Kilibarda, Milan

    “…Crop maps are highly desired information in modern agriculture as they enable possessors to manage their business in the most optimal way. Usually in remote…”
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  5. 5

    Integration of reference data from different Rapid-E devices supports automatic pollen detection in more locations by Matavulj, Predrag, Cristofori, Antonella, Cristofolini, Fabiana, Gottardini, Elena, Brdar, Sanja, Sikoparija, Branko

    Published in The Science of the total environment (10-12-2022)
    “…Pollen is the most common cause of seasonal allergies, affecting over 33 % of the European population, even when considering only grasses. Informing the…”
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  6. 6

    Why should we care about high temporal resolution monitoring of bioaerosols in ambient air? by Smith, Matt, Matavulj, Predrag, Mimić, Gordan, Panić, Marko, Grewling, Łukasz, Šikoparija, Branko

    Published in The Science of the total environment (20-06-2022)
    “…This is the first time that atmospheric concentrations of individual pollen types have been recorded by an automatic sampler with 1-hour and sub-hourly…”
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  7. 7

    Real-time automatic detection of starch particles in ambient air by Šikoparija, Branko, Matavulj, Predrag, Mimić, Gordan, Smith, Matt, Grewling, Łukasz, Podraščanin, Zorica

    Published in Agricultural and forest meteorology (15-08-2022)
    “…•Quantification of starch in ambient air by laser spectroscopy bioaerosol monitoring.•Insights into atmospheric processes via high temporal resolution…”
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  8. 8

    RealForAll: real-time system for automatic detection of airborne pollen by Tešendić, Danijela, Boberić Krstićev, Danijela, Matavulj, Predrag, Brdar, Sanja, Panić, Marko, Minić, Vladan, Šikoparija, Branko

    Published in Enterprise information systems (04-05-2022)
    “…The aim of this paper is to describe a solution suitable for the automation of standard pollen information service (EN 16868:2019). We are describing the…”
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    Classification accuracy and compatibility across devices of a new Rapid-E+ flow cytometer by Sikoparija, Branko, Matavulj, Predrag, Simovic, Isidora, Radisic, Predrag, Brdar, Sanja, Minic, Vladan, Tesendic, Danijela, Kadantsev, Evgeny, Palamarchuk, Julia, Sofiev, Mikhail

    Published in Atmospheric measurement techniques (03-09-2024)
    “…The study evaluated a new model of a Plair SA airflow cytometer, Rapid-E+, and assessed its suitability for airborne pollen monitoring within operational…”
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    Journal Article