"A letűnt világ bürokratáinak porlepte bűnjelei…” Selejtezés és iratmentés Szolnok megyében, az 1950-es években by László Mucsi

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Predicting the future land-use change and evaluating the change in landscape pattern in Binh Duong province, Vietnam by Dang Hung Bui, László Mucsi

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Éljen Sztálin generalisszimusz! – A digitális történetmesélés első kísérlete az MNL Jász-Nagykun-Szolnok Megyei Levéltárában by László Mucsi, Maslowski Madlen Szabóné

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From Land Cover Map to Land Use Map: A Combined Pixel-Based and Object-Based Approach Using Multi-Temporal Landsat Data, a Random Forest Classifier, and Decision Rules by Dang Hung Bui, László Mucsi

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Time-series analysis of Sentinel-2 satellite images for sunflower yield estimation by Khilola Amankulova, Nizom Farmonov, László Mucsi

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Sunflower crop yield prediction by advanced statistical modeling using satellite-derived vegetation indices and crop phenology by Khilola Amankulova, Nizom Farmonov, Uzbekkhon Mukhtorov, László Mucsi

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Improvement in Satellite Image-Based Land Cover Classification with Landscape Metrics by András Gudmann, Nándor Csikós, Péter Szilassi, László Mucsi

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Comparison of PlanetScope, Sentinel-2, and landsat 8 data in soybean yield estimation within-field variability with random forest regression by Khilola Amankulova, Nizom Farmonov, Parvina Akramova, Ikrom Tursunov, László Mucsi

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The evaluation and application of an urban land cover map with image data fusion and laboratory measurements by László Mucsi, Csilla Mariann Liska, László Henits, Zalán Tobak, Bálint Csendes, László Nagy

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Combining PlanetScope and Sentinel-2 images with environmental data for improved wheat yield estimation by Nizom Farmonov, Khilola Amankulova, József Szatmári, Jamol Urinov, Zafar Narmanov, Jakhongir Nosirov, László Mucsi

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Crop Type Classification by DESIS Hyperspectral Imagery and Machine Learning Algorithms by Nizom Farmonov, Khilola Amankulova, Jozsef Szatmari, Alireza Sharifi, Dariush Abbasi-Moghadam, Seyed Mahdi Mirhoseini Nejad, Laszlo Mucsi

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Effectiveness of machine learning and deep learning models at county-level soybean yield forecasting by Nizom Farmonov, Khilola Amankulova, Shahid Nawaz Khan, Mokhigul Abdurakhimova, József Szatmári, Tukhtaeva Khabiba, Radjabova Makhliyo, Meiliyeva Khodicha, László Mucsi

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