| Convolutional neural networks for texture feature extraction. Applications to leaf disease classification in precision agriculture S Barburiceanu, S Meza, B Orza, R Malutan, R Terebes IEEE Access 9, 160085-160103, 2021 | 68 | 2021 |
| 3D texture feature extraction and classification using GLCM and LBP-based descriptors S Barburiceanu, R Terebes, S Meza Applied Sciences 11 (5), 2332, 2021 | 46 | 2021 |
| Grape leaf disease classification using LBP-derived texture operators and colour S Barburiceanu, R Terebes, S Meza 2020 IEEE International Conference on Automation, Quality and Testing …, 2020 | 14 | 2020 |
| An improved feature extraction method for texture classification with increased noise robustness SR Barburiceanu, S Meza, C Germain, R Terebes 2019 27th European Signal Processing Conference (EUSIPCO), 1-5, 2019 | 14 | 2019 |
| Hyperspectral Image Classification using the MRELBP Texture Descriptor S Barburiceanu, R Terebes, S Meza 2019 E-Health and Bioengineering Conference (EHB), 1-6, 2019 | 6 | 2019 |
| Improved 3d co-occurrence matrix for texture description and classification S Barburiceanu, R Terebes, S Meza 2020 International Symposium on Electronics and Telecommunications (ISETC), 1-4, 2020 | 5 | 2020 |
| Automatic detection of melanoma by deep learning models-based feature extraction and fine-tuning strategy S Barburiceanu, R Terebeș IOP Conference Series: Materials Science and Engineering 1254 (1), 012035, 2022 | 4 | 2022 |
| 3D Texture Feature Extraction and Classification using the BM3DELBP approach S Barburiceanu, R Terebes, S Meza 2020 IEEE 16th International Conference on Intelligent Computer …, 2020 | 4 | 2020 |
| Plant Disease Classification Using Texture And Colour S Barburiceanu, R Terebes Acta Technica Napocensis 61 (1), 21-28, 2021 | 2 | 2021 |
| Feature Extraction Methods Based on Deep-Learning Approaches. Application To Automatic Diagnosis of Breast Cancer RT Stefania Barburiceanu Acta Technica Napocensis Electronics and Telecommunications 62 (1), 2022 | 1* | 2022 |
| Histogram Equalization M Borda, R Terebes, R Malutan, I Ilea, M Cislariu, A Miclea, ... Randomness and Elements of Decision Theory Applied to Signals, 165-171, 2021 | 1 | 2021 |
| Data Analytics of Gait Monitoring from Parkinson's Disease Patients R Malutan, AV Miclea, S Barburiceanu, DT Oltean 2022 E-Health and Bioengineering Conference (EHB), 1-4, 2022 | | 2022 |
| DEEP LEARNING STRATEGIES BASED ON FINE-TUNING. APPLICATION TO MEDICAL IMAGE CLASSIFICATION. S Barburiceanu, A Miclea, R Terebes Acta Technica Napocensis. Electronica-Telecomunicatii 62 (2), 2022 | | 2022 |
| Probability Distributions M Borda, R Terebes, R Malutan, I Ilea, M Cislariu, A Miclea, ... Randomness and Elements of Decision Theory Applied to Signals, 17-33, 2021 | | 2021 |
| Random Processes M Borda, R Terebes, R Malutan, I Ilea, M Cislariu, A Miclea, ... Randomness and Elements of Decision Theory Applied to Signals, 49-66, 2021 | | 2021 |
| Comparison of ICA Algorithms for Oligonucleotide Microarray Data M Borda, R Terebes, R Malutan, I Ilea, M Cislariu, A Miclea, ... Randomness and Elements of Decision Theory Applied to Signals, 137-155, 2021 | | 2021 |
| Texture Feature Extraction and Classification Using the Local Binary Patterns Operator M Borda, R Terebes, R Malutan, I Ilea, M Cislariu, A Miclea, ... Randomness and Elements of Decision Theory Applied to Signals, 191-204, 2021 | | 2021 |
| PCM and DPCM–Applications in Image Processing M Borda, R Terebes, R Malutan, I Ilea, M Cislariu, A Miclea, ... Randomness and Elements of Decision Theory Applied to Signals, 173-184, 2021 | | 2021 |
| Decision Systems in Noisy Transmission Channels M Borda, R Terebes, R Malutan, I Ilea, M Cislariu, A Miclea, ... Randomness and Elements of Decision Theory Applied to Signals, 111-135, 2021 | | 2021 |
| Noise in Telecommunication Systems M Borda, R Terebes, R Malutan, I Ilea, M Cislariu, A Miclea, ... Randomness and Elements of Decision Theory Applied to Signals, 89-109, 2021 | | 2021 |
Terebes RomulusTechnical University of Cluj-NapocaVerified email at com.utcluj.ro
