J – Journal publications, C – Conference proceedings, A – Abstracts




[C1] Grbovic, Z., Panic, M., Marko, O., Brdar, S. and Crnojevic, V., 2019. Wheat ear detection in RGB and thermal images using deep neural networks. 15th International Conference on Machine Learning and Data Mining MLDM 2019


[J1] Samourkasidis, A and Ioannis N. Athanasiadis. “A semantic approach for time series data fusion.” Computers and Electronics in Agriculture 169 (2020): 105171. compag.2019.105171 


[J2] Popović, V., Ljubičić, N., Kostić, M., Radulović, M., Blagojević, D., Ugrenović, V., Popović, D. and Ivošević, B., 2020. Genotype× Environment Interaction for Wheat Yield Traits Suitable for Selection in Different Seed Priming Conditions. Plants, 9(12), p.1804. /plants9121804 3


[J3] Pandžić, M., Ljubičić, N., Mimić, G., Pandžić, J., Pejak, B. and Crnojević, V., 2020. A Case Study of Monitoring Maize Dynamics in Serbia by Utilizing SENTINEL-1 Data and Growing Degree Days. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 3, pp.117-124. 


[J4] Ljubičić, N., Radović, M., Kostić, M., Popović, V., Radulović, M., Blagojević, D. and Ivošević, B., 2020. THE IMPACT OF ZnO NANOPARTICLES APPLICATION ON YIELD COMPONENTS OF DIFFERENT WHEAT GENOTYPES. Poljoprivreda i Sumarstvo, 66(2), pp.217-227, 10.17707/AgricultForest.66.2.19


[C2] Ljubičić, N., Popović, V., Kostić, M., Radović, M., Radulović, M., Blagojević, D., Ivošević, B. Association of canopy spectral reflectance indices and yield components of winter wheat (Triticum aestivum L.). Proceedings of II. International Agricultural, Biological & Life Science Conference, Edirne, Turkey, 1-3 September, 2020, 298-308.


[J5] Pylianidis, C., Osinga, S. and Athanasiadis, I.N., 2021. Introducing digital twins to agriculture. Computers and Electronics in Agriculture, 184, p.105942. 


[A1] Pavlovic, D., Tachtatzis, C., Hamilton, A., Marko, O., Atkinson, R., Davison, C., Michie, C., Crnojevic, V., & Andonovic, I. (2020). Classification of cattle behaviour using convolutional neural networks.  In European Federation of Animal Science (EAAP) Annual Meeting.


[J6]  Pylianidis, C., Snow, V., Holzworth, D., Bryant, J. & Athanasiadis, I. N., Location-specific vs location-agnostic machine learning metamodels for predicting pasture nitrogen response rate, Lecture Notes in Computer Science, 12666, p. 45-54. 


[J7] C.A. Midingoyi, C. Pradal, I.N. Athanasiadis, M. Donatelli, A. Enders, D. Fumagalli, F. Garcia, D. Holzworth, G. Hoogenboom, C. Porter, H. Raynal, P. Thorburn, P. Martre, Reuse of process-based models: automatic transformation into many programming languages and simulation platforms, in silico Plants, 2(1):diaa007, 2020, doi:10.1093/insilicoplants/diaa007 .


[J8] Pavlovic, D.; Davison, C.; Hamilton, A.; Marko, O.; Atkinson, R.; Michie, C.; Crnojevic, V.; Andonovic, I.; Bellekens, X.; Tachtatzis, C. Classification of Cattle Behaviours Using Neck-Mounted Accelerometer-Equipped Collars and Convolutional Neural Networks. Sensors 2021, 21, 4050.


[A2] Radulovic, M., Stojkovic, S., Pejak, B., Lugonja, P., Brdar, S., Marko, O., Pavic, D., Crnojevic, V., Classification of irrigated and rainfed croplands in Vojvodina Province (North Serbia) using Sentinel-2 data, EFITA 2021


[C3] Matavulj. P., Brdar., S., Racković, M., Šikoparija, B.,  Athanasiadis, I.N., Domain adaptation with unlabeled data for model transferability between airborne particle identifiers, 17th International Conference on Machine Learning and Data Mining MLDM 2021


[J9] Kostić, M.M., Tagarakis, A.C., Ljubičić, N., Blagojević, D., Radulović, M., Ivošević, B. and Rakić, D., 2021. The Effect of N Fertilizer Application Timing on Wheat Yield on Chernozem Soil. Agronomy, 11(7), p.1413.


[J10] Ivošević, B., Lugonja, P., Brdar, S., Radulović, M., Vujić, A. and Valente, J., 2021. UAV-Based Land Cover Classification for Hoverfly (Diptera: Syrphidae) Habitat Condition Assessment: A Case Study on Mt. Stara Planina (Serbia). Remote Sensing, 13(16), p.3272.


[C4] Filipović, V., Panić, M., Brdar, S. and Brkljač, B., 2021, September. Significance of Morphological Features in Rice Variety Classification Using Hyperspectral Imaging. In 2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA) (pp. 171-176). IEEE.


[A3] Marinković D., Ćirić V., Benka P., Marko O., Nešić Lj., THE IMPORTANCE OF SOIL DATA UNIFICATION FROM SERBIAN AGRICULTURAL ADVISORY SERVICES AND ACCOMPANYING PROBLEMS, 3rd International and 15th National Congress, Serbian Society of Soil Science, Book of abstracts, pp 69-69, ISBN -979-86-912877-4-0, Sokobanja, 21-24 September, 2021




Under review


[J8] Filipović, N., Brdar, S., Marko, O., Crnojević V., Regional Soil Moisture Prediction System based on Long Short-Term Memory Network, submitted to Computers and Electronics in Agriculture


Data sets


[D1] Pavlovic, Dejan, Christopher Davison, Andrew Hamilton, Oskar Marko, Robert Atkinson, Craig Michie, … Tachtatzis, Christos. (2021). Precision Beef – Animal Behaviour Classification [Data set]. Zenodo.


References on DRAGON project 

Bacco, M., Barsocchi, P., Ferro, E., Gotta, A. and Ruggeri, M., 2019. The digitisation of agriculture: a survey of research activities on smart farming. Array, 3, p.100009.