Idrid: Diabetic retinopathy–segmentation and grading challenge P Porwal, S Pachade, M Kokare, G Deshmukh, J Son, W Bae, L Liu, ... Medical image analysis 59, 101561, 2020 | 259 | 2020 |
Classification of skin lesions using an ensemble of deep neural networks B Harangi, A Baran, A Hajdu 2018 40th annual international conference of the IEEE engineering in …, 2018 | 99 | 2018 |
On modelling discrete geological structures as Markov random fields T Norberg, L Rosén, A Baran, S Baran Mathematical Geology 34, 63-77, 2002 | 84 | 2002 |
Automatic screening of fundus images using a combination of convolutional neural network and hand-crafted features B Harangi, J Toth, A Baran, A Hajdu 2019 41st Annual international conference of the IEEE engineering in …, 2019 | 70 | 2019 |
Assisted deep learning framework for multi-class skin lesion classification considering a binary classification support B Harangi, A Baran, A Hajdu Biomedical Signal Processing and Control 62, 102041, 2020 | 61 | 2020 |
Gauss-Legendre elements: a stable, higher order non-conforming finite element family Á Baran, G Stoyan Computing 79, 1-21, 2007 | 41 | 2007 |
Machine learning for total cloud cover prediction A Baran, S Lerch, M El Ayari, S Baran Neural Computing and Applications 33 (7), 2605-2620, 2021 | 35 | 2021 |
Crouzeix-Velte decompositions for higher-order finite elements G Stoyan, Á Baran Computers & Mathematics with Applications 51 (6-7), 967-986, 2006 | 34 | 2006 |
Sorption and gas sensitive properties of In2O3 based ceramics doped with Ga2O3 A Ratko, O Babushkin, A Baran, S Baran Journal of the European Ceramic Society 18 (14), 2227-2232, 1998 | 29 | 1998 |
On the origin of 1.5 μm luminescence in porous silicon coated with sol–gel derived erbium-doped Fe2O3 films NV Gaponenko, AV Mudryi, OV Sergeev, M Stepikhova, L Palmetshofer, ... Journal of luminescence 80 (1-4), 399-403, 1998 | 19 | 1998 |
Calibration of wind speed ensemble forecasts for power generation S Baran, Á Baran arXiv preprint arXiv:2104.14910, 2021 | 18 | 2021 |
Analytical solutions for the radial Scarf II potential G Lévai, Á Baran, P Salamon, T Vertse Physics Letters A 381 (23), 1936-1942, 2017 | 14 | 2017 |
Distributions of the S-matrix poles in Woods–Saxon and cut-off Woods–Saxon potentials P Salamon, Á Baran, T Vertse Nuclear Physics A 952, 1-17, 2016 | 13 | 2016 |
Statistical post‐processing of heat index ensemble forecasts: Is there a royal road? S Baran, Á Baran, F Pappenberger, Z Ben Bouallegue Quarterly Journal of the Royal Meteorological Society 146 (732), 3416-3434, 2020 | 11 | 2020 |
Elementary numerical mathematics for programmers and engineers G Stoyan, A Baran Springer International Publishing, 2016 | 7 | 2016 |
Generalizations to discrete and analytical Crouzeix–Velte decompositions G Stoyan, G Strauber, Á Baran Numerical Linear Algebra with Applications 11 (5‐6), 565-590, 2004 | 6 | 2004 |
A two‐step machine‐learning approach to statistical post‐processing of weather forecasts for power generation Á Baran, S Baran Quarterly Journal of the Royal Meteorological Society 150 (759), 1029-1047, 2024 | 4 | 2024 |
A two-step machine learning approach to statistical post-processing of weather forecasts for power generation Á Baran, S Baran arXiv preprint arXiv:2207.07589, 2022 | 3 | 2022 |
JOZSO, a computer code for calculating broad neutron resonances in phenomenological nuclear potentials Á Baran, C Noszály, T Vertse Computer Physics Communications 228, 185-191, 2018 | 3 | 2018 |
Matching polynomial tails to the cut-off Woods–Saxon potential Á Baran, T Vertse International Journal of Modern Physics E 26 (11), 1750078, 2017 | 2 | 2017 |