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Investigating machine learning techniques for MRI-based classification of brain neoplasms.

, , and . Int. J. Comput. Assist. Radiol. Surg., 6 (6): 821-828 (2011)

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Investigating machine learning techniques for MRI-based classification of brain neoplasms., , and . Int. J. Comput. Assist. Radiol. Surg., 6 (6): 821-828 (2011)Time-Varying Parametric Modeling of ECoG for Syllable Decoding., , , , , and . BIH, volume 9250 of Lecture Notes in Computer Science, page 222-231. Springer, (2015)Real-time voice activity detection for ECoG-based speech brain machine interfaces., , , , , and . DSP, page 862-865. IEEE, (2014)On the development of brain quantum-computer interfaces., , and . ICARCV, page 239-242. IEEE, (2014)Optimal selection of electrocorticographic sensors for voice activity detection., , , , , and . ICARCV, page 29-32. IEEE, (2014)Combining Active Learning with Self-train algorithm for classification of multimodal problems., , , , and . IISA, page 1-8. IEEE, (2019)Combination of Active Learning and Semi-Supervised Learning under a Self-Training Scheme., , , , and . Entropy, 21 (10): 988 (2019)Classification of epileptic and non-epileptic events using tensor decomposition., , , , , and . BIBE, page 1-5. IEEE Computer Society, (2015)Spatio-spectral analysis of ECoG signals during voice activity., , , , , and . BIBE, page 1-4. IEEE Computer Society, (2013)A low cost approach for brain tumor segmentation based on intensity modeling and 3D Random Walker., , , , and . Biomed. Signal Proc. and Control, (2015)