| Convolutional neural networks based efficient approach for classification of lung diseases F Demir, A Sengur, V Bajaj Health information science and systems 8 (1), 4, 2019 | 187 | 2019 |
| A new deep CNN model for environmental sound classification F Demir, DA Abdullah, A Sengur IEEE Access 8, 66529-66537, 2020 | 130 | 2020 |
| Classification of Lung Sounds With CNN Model Using Parallel Pooling Structure F Demir, AM Ismael, A Sengur IEEE Access 8, 105376-105383, 2020 | 119 | 2020 |
| DeepCoroNet: A deep LSTM approach for automated detection of COVID-19 cases from chest X-ray images F Demir Applied soft computing 103, 107160, 2021 | 114 | 2021 |
| A new pyramidal concatenated CNN approach for environmental sound classification F Demir, M Turkoglu, M Aslan, A Sengur Applied Acoustics 170, 107520, 2020 | 106 | 2020 |
| Towards the classification of heart sounds based on convolutional deep neural network F Demir, A Şengür, V Bajaj, K Polat Health information science and systems 7, 1-9, 2019 | 85 | 2019 |
| Exploring deep learning features for automatic classification of human emotion using EEG rhythms F Demir, N Sobahi, S Siuly, A Sengur IEEE Sensors Journal 21 (13), 14923-14930, 2021 | 83 | 2021 |
| Surface EMG signals and deep transfer learning-based physical action classification F Demir, V Bajaj, MC Ince, S Taran, A Şengür Neural Computing and Applications 31, 8455-8462, 2019 | 74 | 2019 |
| The effect of personal, familial, and environmental characteristics on acne vulgaris: a prospective, multicenter, case controlled study. AS Karadağ, I Balta, H Saricaoğlu, S Kilic, KH Kelekçi, M Yildirim, ... Giornale italiano di dermatologia e venereologia: organo ufficiale, Societa …, 2017 | 52 | 2017 |
| Improving brain tumor classification performance with an effective approach based on new deep learning model named 3ACL from 3D MRI data F Demir, Y Akbulut, B Taşcı, K Demir Biomedical Signal Processing and Control 81, 104424, 2023 | 45 | 2023 |
| Environmental sound classification using optimum allocation sampling based empirical mode decomposition S Ahmad, S Agrawal, S Joshi, S Taran, V Bajaj, F Demir, A Sengur Physica A: Statistical Mechanics and its Applications 537, 122613, 2020 | 39 | 2020 |
| An effective and robust approach based on r-cnn+ lstm model and ncar feature selection for ophthalmological disease detection from fundus images F Demir, B Taşcı Journal of Personalized Medicine 11 (12), 1276, 2021 | 38 | 2021 |
| Deep autoencoder-based automated brain tumor detection from MRI data F Demir Elsevier 1, 317-351, 2022 | 32 | 2022 |
| DeepBreastNet: A novel and robust approach for automated breast cancer detection from histopathological images F Demir Biocybernetics and biomedical engineering 41 (3), 1123-1139, 2021 | 32 | 2021 |
| Low level texture features for snore sound discrimination F Demir, A Sengur, N Cummins, S Amiriparian, B Schuller 2018 40th Annual international conference of the IEEE engineering in …, 2018 | 28 | 2018 |
| Automated steel surface defect detection and classification using a new deep learning-based approach K Demir, M Ay, M Cavas, F Demir Neural Computing and Applications 35 (11), 8389-8406, 2023 | 26 | 2023 |
| Feature mapping and deep long short term memory network-based efficient approach for Parkinson’s disease diagnosis F Demir, A Sengur, A Ari, K Siddique, M Alswaitti IEEE Access 9, 149456-149464, 2021 | 23 | 2021 |
| A simple and effective approach based on a multi-level feature selection for automated Parkinson’s disease detection F Demir, K Siddique, M Alswaitti, K Demir, A Sengur Journal of Personalized Medicine 12 (1), 55, 2022 | 18 | 2022 |
| DeepCov19Net: Automated COVID-19 Disease Detection with a Robust and Effective Technique Deep Learning Approach F Demir, K Demir, A Şengür New Generation Computing 40, 1053-1075, 2022 | 17 | 2022 |
| A new deep technique using R-CNN model and L1NSR feature selection for brain MRI classification F Demir, Y Akbulut Biomedical Signal Processing and Control 75, 103625, 2022 | 16 | 2022 |
Abdulkadir SengurFirat UniversityVerified email at firat.edu.tr
