Rahul Paul
Cited by
Cited by
Deep feature transfer learning in combination with traditional features predicts survival among patients with lung adenocarcinoma
R Paul, SH Hawkins, Y Balagurunathan, MB Schabath, RJ Gillies, LO Hall, ...
Tomography 2 (4), 388, 2016
Predicting malignant nodules by fusing deep features with classical radiomics features
R Paul, S Hawkins, MB Schabath, RJ Gillies, LO Hall, DB Goldgof
Journal of Medical Imaging 5 (1), 011021, 2018
Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT
R Paul, SH Hawkins, LO Hall, DB Goldgof, RJ Gillies
2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2016
Finding covid-19 from chest x-rays using deep learning on a small dataset
LO Hall, R Paul, DB Goldgof, GM Goldgof
arXiv preprint arXiv:2004.02060, 2020
Predicting nodule malignancy using a CNN ensemble approach
R Paul, L Hall, D Goldgof, M Schabath, R Gillies
2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018
A study on validating non-linear dimensionality reduction using persistent homology
R Paul, SK Chalup
Pattern Recognition Letters 100, 160-166, 2017
Convolutional neural networks for neonatal pain assessment
G Zamzmi, R Paul, MS Salekin, D Goldgof, R Kasturi, T Ho, Y Sun
IEEE Transactions on Biometrics, Behavior, and Identity Science 1 (3), 192-200, 2019
Explaining deep features using Radiologist-Defined semantic features and traditional quantitative features
R Paul, M Schabath, Y Balagurunathan, Y Liu, Q Li, R Gillies, LO Hall, ...
Tomography 5 (1), 192, 2019
Classifying cooking object's state using a tuned VGG convolutional neural network
R Paul
arXiv preprint arXiv:1805.09391, 2018
Pain assessment from facial expression: Neonatal convolutional neural network (N-CNN)
G Zamzmi, R Paul, D Goldgof, R Kasturi, Y Sun
2019 International Joint Conference on Neural Networks (IJCNN), 1-7, 2019
Stability of deep features across CT scanners and field of view using a physical phantom
R Paul, M Shafiq-ul-Hassan, EG Moros, RJ Gillies, LO Hall, DB Goldgof
Medical Imaging 2018: Computer-Aided Diagnosis 10575, 105753P, 2018
Make your bone great again: A study on osteoporosis classification
R Paul, S Alahamri, S Malla, GJ Quadri
arXiv preprint arXiv:1707.05385, 2017
Mitigating adversarial attacks on medical image understanding systems
R Paul, M Schabath, R Gillies, L Hall, D Goldgof
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1517-1521, 2020
Behind the Mask: Understanding the Structural Forces That Make Social Graphs Vulnerable to Deanonymization.
S Horawalavithana, JA Flores, J Skvoretz, A Iamnitchi
IEEE Trans. Comput. Soc. Syst. 6 (6), 1343-1356, 2019
Deep feature stability analysis using CT images of a physical phantom across scanner manufacturers, cartridges, pixel sizes, and slice thickness
R Paul, MS Hassan, EG Moros, RJ Gillies, LO Hall, DB Goldgof
Tomography 6 (2), 250, 2020
Lung nodule sizes are encoded when scaling CT image for CNN's
D Cherezov, R Paul, N Fetisov, RJ Gillies, MB Schabath, DB Goldgof, ...
Tomography 6 (2), 209, 2020
Hybrid models for lung nodule malignancy prediction utilizing convolutional neural network ensembles and clinical data
R Paul, MB Schabath, R Gillies, LO Hall, DB Goldgof
Journal of Medical Imaging 7 (2), 024502, 2020
Towards deep radiomics: nodule malignancy prediction using CNNs on feature images
R Paul, D Cherezov, MB Schabath, RJ Gillies, LO Hall, DB Goldgof
Medical Imaging 2019: Computer-Aided Diagnosis 10950, 109503Z, 2019
Representation of Deep Features using Radiologist defined Semantic Features
R Paul, Y Liu, Q Li, L Hall, D Goldgof, Y Balagurunathan, M Schabath, ...
2018 International Joint Conference on Neural Networks (IJCNN), 1-7, 2018
Fuzzy Set Similarity for Feature Selection in Classification
V Cross, M Zmuda, R Paul, L Hall
2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8, 2020
The system can't perform the operation now. Try again later.
Articles 1–20