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Machine Learning-based EEG Applications and Markets
Based on our survey, more research on machine learning-based EEG applications will lead to a more robust EEG-related market.
EEG Machine Learning for Analysis of Mild Traumatic Brain Injury: A survey
We reviewed, summarized, and compared the fourteen most cutting-edge machine learning research papers for predicting and classifying mTBI in terms of 1) EEG data types, 2) data preprocessing methods, 3) machine learning feature representations, 4) feature extraction methods, and 5) machine learning classifiers and predictions.
Stereo Dense Scene Reconstruction and Accurate Localization for Learning-Based Navigation of Laparoscope in Minimally Invasive Surgery
Then, we develop a dense visual reconstruction algorithm to represent the scene by surfels, estimate the laparoscope poses and fuse the depth maps into a unified reference coordinate for tissue reconstruction.
Highly Efficient Architecture of NewHope-NIST on FPGA using Low-Complexity NTT/INTT
First, both the pre-processing of NTT and the post-processing of INTT are merged into the fast Fourier transform (FFT) algorithm, which reduces N and 2N modular multiplications for N-point NTT and INTT, respectively.
