Pattern Recognition with Fuzzy Objective Function Algorithms

Community detection in graphs

Fortunato, S. (2010) · Physics Reports · doi:10.1016/j.physrep.2009.11.002 · Cited by 11,293

A nonparametric method for automatic correction of intensity nonuniformity in MRI data

Sled, J. G., Zijdenbos, A. P., & Evans, A. C. (1998) · IEEE Transactions on Medical Imaging · doi:10.1109/42.668698 · Cited by 4,731

An entropy criterion for assessing the number of clusters in a mixture model

Celeux, G., & Soromenho, G. (1996) · Journal of Classification · doi:10.1007/bf01246098 · Cited by 2,448

A Comprehensive Survey of Clustering Algorithms

Xu, D., & Tian, Y. (2015) · Annals of Data Science · doi:10.1007/s40745-015-0040-1 · Cited by 1,939

A review of novelty detection

Pimentel, M. A. F., Clifton, D. A., Clifton, L., & Tarassenko, L. (2014) · Signal Processing · doi:10.1016/j.sigpro.2013.12.026 · Cited by 1,649

Chronic neural recordings using silicon microelectrode arrays electrochemically deposited with a poly(3,4-ethylenedioxythiophene) (PEDOT) film

Ludwig, K. A., Uram, J. D., Yang, J., Martin, D. C., & Kipke, D. R. (2006) · Journal of Neural Engineering · doi:10.1088/1741-2560/3/1/007 · Cited by 638

A Review of Nonlinear Hyperspectral Unmixing Methods

Heylen, R., Parente, M., & Gader, P. (2014) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2014.2320576 · Cited by 591

Connectivity-based subdivisions of the human right “temporoparietal junction area”: evidence for different areas participating in different cortical networks

Mars, R. B., Sallet, J., Schuffelgen, U., Jbabdi, S., Toni, I., & Rushworth, M. F. S. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhr268 · Cited by 520

A heuristic fuzzy logic approach to EMG pattern recognition for multifunctional prosthesis control

Ajiboye, A. B., & Weir, R. F. (2005) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2005.847357 · Cited by 415

Big data: From beginning to future

Yaqoob, I., Hashem, I. A. T., Gani, A., Mokhtar, S., Ahmed, E., Anuar, N. B., & Vasilakos, A. V. (2016) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2016.07.009 · Cited by 410

Automatic breast ultrasound image segmentation: a survey

Xian, M., Zhang, Y., Cheng, H. D., Xu, F., Zhang, B., & Ding, J. (2018) · Pattern Recognition · doi:10.1016/j.patcog.2018.02.012 · Cited by 284

Feature learning and change feature classification based on deep learning for ternary change detection in SAR images

Gong, M., Yang, H., & Zhang, P. (2017) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2017.05.001 · Cited by 226

An expert system for brain tumor detection: Fuzzy C-means with super resolution and convolutional neural network with extreme learning machine

Özyurt, F., Sert, E., & Avcı, D. (2020) · Medical Hypotheses · doi:10.1016/j.mehy.2019.109433 · Cited by 210

Quantum neural networks (QNNs): inherently fuzzy feedforward neural networks

Purushothaman, G., & Karayiannis, N. B. (1997) · IEEE Transactions on Neural Networks · doi:10.1109/72.572106 · Cited by 163

Probabilistic D-Clustering

Ben-Israel, A., & Iyigun, C. (2008) · Journal of Classification · doi:10.1007/s00357-008-9002-z · Cited by 74

Segmentation of Dual-Axis Swallowing Accelerometry Signals in Healthy Subjects With Analysis of Anthropometric Effects on Duration of Swallowing Activities

Sejdic, E., Steele, C. M., & Chau, T. (2009) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2008.2010504 · Cited by 73

Steel Surface Defect Detection Using Texture Segmentation Based on Multifractal Dimension

Yazdchi, M., Yazdi, M., & Mahyari, A. G. (2009) · 2009 International Conference on Digital Image Processing · doi:10.1109/icdip.2009.68 · Cited by 65

A review of Methods for Bias Correction in Medical Images

Song, S., Zheng, Y., & He, Y. (2017) · Biomedical Engineering Review · doi:10.18103/bme.v3i1.1550 · Cited by 62

The sensitivity of simulated streamflow to individual hydrologic processes across North America

Mai, J., Craig, J. R., Tolson, B. A., & Arsenault, R. (2022) · Nature Communications · doi:10.1038/s41467-022-28010-7 · Cited by 63

Swarm Intelligence Techniques in Recommender Systems-a Review of Recent Research

Peška, L., Tashu, T. M., & Horváth, T. (2019) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2019.04.003 · Cited by 54

Robust Fuzzy Principal Component Analysis (FPCA). A Comparative Study Concerning Interaction of Carbon−Hydrogen Bonds with Molybdenum−Oxo Bonds

Cundari, T. R., Sârbu, C., & Pop, H. F. (2002) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci025524s · Cited by 53

Detection and Classification of Surface Defects of Cold Rolling Mill Steel Using Morphology and Neural Network

Yazdchi, M. R., Mahyari, A. G., & Nazeri, A. (2008) · 2008 International Conference on Computational Intelligence for Modelling Control & Automation · doi:10.1109/cimca.2008.130 · Cited by 39

SimplePPT: A Simple Principal Tree Algorithm

Mao, Q., Yang, L., Wang, L., Goodison, S., & Sun, Y. (2015) · Proceedings of the 2015 SIAM International Conference on Data Mining · doi:10.1137/1.9781611974010.89 · Cited by 33

A review of computational intelligence techniques in coral reef-related applications

Salcedo-Sanz, S., Cuadra, L., & Vermeij, M. J. A. (2016) · Ecological Informatics · doi:10.1016/j.ecoinf.2016.01.008 · Cited by 27

Semantic segmentation based on Deep learning for the detection of Cyanobacterial Harmful Algal Blooms (CyanoHABs) using synthetic images

Barrientos-Espillco, F., Gascó, E., López-González, C. I., Gómez-Silva, M. J., & Pajares, G. (2023) · Applied Soft Computing · doi:10.1016/j.asoc.2023.110315 · Cited by 26

Hidden information on protein function in censuses of proteome foldedness

Cox, D., Ang, C.-S., Nillegoda, N. B., Reid, G. E., & Hatters, D. M. (2022) · Nature Communications · doi:10.1038/s41467-022-29661-2 · Cited by 16

Segmentation and Boundary Detection of Fetal Kidney Images in Second and Third Trimesters Using Kernel-Based Fuzzy Clustering

Meenakshi, S., Suganthi, M., & Sureshkumar, P. (2019) · Journal of Medical Systems · doi:10.1007/s10916-019-1324-3 · Cited by 15

Omnidirectional and omnifunctional connectivity analyses with a diverse species pool

Tessier, D. L., Maranger, R., & Poisot, T. (2020) · bioRxiv · doi:10.1101/2020.02.03.932095 · Cited by 4