Results 261 to 270 of about 757,511 (305)

Comparison of text preprocessing methods

Natural Language Engineering, 2022
Text preprocessing is not only an essential step to prepare the corpus for modeling but also a key area that directly affects the natural language processing (NLP) application results.
Christine P. Chai
semanticscholar   +1 more source

FMRIPrep: a robust preprocessing pipeline for functional MRI

Nature Methods, 2018
Preprocessing of functional magnetic resonance imaging (fMRI) involves numerous steps to clean and standardize the data before statistical analysis. Generally, researchers create ad hoc preprocessing workflows for each dataset, building upon a large ...
O. Esteban, Christopher J. Markiewicz, Ross W. Blair, C. Moodie, A. I. Isik, Asier Erramuzpe, James D. Kent, M. Goncalves, E. Dupre, Madeleine C. Snyder, H. Oya, Satrajit S. Ghosh, Jessey Wright, Joke Durnez, R. Poldrack, Krzysztof J. Gorgolewski   +15 more
semanticscholar   +1 more source

A Survey of Modulation Classification Using Deep Learning: Signal Representation and Data Preprocessing

IEEE Transactions on Neural Networks and Learning Systems, 2021
Modulation classification is one of the key tasks for communications systems monitoring, management, and control for addressing technical issues, including spectrum awareness, adaptive transmissions, and interference avoidance.
Shengliang Peng, Shujun Sun, Yu-dong Yao
semanticscholar   +1 more source

Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers

Speech Communication, 2020
Speech is the most natural way of expressing ourselves as humans. It is only natural then to extend this communication medium to computer applications. We define speech emotion recognition (SER) systems as a collection of methodologies that process and ...
Mehmet Berkehan Akçay, Kaya Oğuz
semanticscholar   +1 more source

A methodological approach to preprocessing FTIR spectra of adulterated sesame oil.

Food Chemistry, 2023
Fourier transform infrared (FTIR) spectroscopy is established as an effective and fast method for the confirmation of the authenticity of food and among other, edible oils. However, no standard procedure is available for applying preprocessing as a vital
R. Khodabakhshian, Hajarsadat Seyedalibeyk Lavasani, P. Weller   +2 more
semanticscholar   +1 more source

Text Preprocessing for Text Mining in Organizational Research: Review and Recommendations

Organizational Research Methods, 2020
Recent advances in text mining have provided new methods for capitalizing on the voluminous natural language text data created by organizations, their employees, and their customers.
Louis Hickman, Stuti Thapa, L. Tay, Mengyang Cao, P. Srinivasan   +4 more
semanticscholar   +1 more source

Cascaded Deep Convolutional Neural Networks as Improved Methods of Preprocessing Raman Spectroscopy Data.

Analytical Chemistry, 2022
Machine learning has had a significant impact on the value of spectroscopic characterization tools, particularly in biomedical applications, due to its ability to detect latent patterns within complex spectral data.
M. Kazemzadeh, M. Martínez-Calderón, Weiliang Xu, L. Chamley, Colin L. Hisey, N. Broderick   +5 more
semanticscholar   +1 more source

Auto-Prep: Efficient and Automated Data Preprocessing Pipeline

IEEE Access, 2022
Data preprocessing is crucial in the Machine Learning pipeline because the models’ learning ability directly affects the quality of data and the underlying information acquired from this stage.
Mehwish Bilal, Ghulam Ali, M. W. Iqbal, Muhammad Anwar, M. S. A. Malik, R. A. Kadir   +5 more
semanticscholar   +1 more source

Energy Theft Detection Using Gradient Boosting Theft Detector With Feature Engineering-Based Preprocessing

IEEE Transactions on Smart Grid, 2019
For the smart grid energy theft identification, this letter introduces a gradient boosting theft detector (GBTD) based on the three latest gradient boosting classifiers (GBCs): 1) extreme gradient boosting; 2) categorical boosting; and 3) light gradient ...
Rajiv Punmiya, S. Choe
semanticscholar   +1 more source

Data Preprocessing

Data Mining and Data Warehousing, 2019
Today's real-world databases are highly susceptible to noisy, missing, and inconsistent data due to their typically huge size (often several gigabytes or more) and their likely origin from multiple, heterogenous sources. Low-quality data will lead to low-
Matteo Ceccarello
semanticscholar   +1 more source