Learning deep forest for face anti-spoofing: An alternative to the neural network against adversarial attacks by Rizhao Cai, Liepiao Zhang, Changsheng Chen, Yongjian Hu, Alex Kot

“…Our approach introduces a multi-scale texture representation based on local binary patterns (LBP) as the model input, replacing the grained-scanning mechanism (GSM) used in the traditional deep forest model. …”
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sEMG-Based Gesture Recognition Using Sigimg-GADF-MTF and Multi-Stream Convolutional Neural Network by Ming Zhang, Leyi Qu, Weibiao Wu, Gujing Han, Wenqiang Zhu

“…To comprehensively leverage the temporal, static, and dynamic information features of multi-channel surface electromyography (sEMG) signals for gesture recognition, considering the sensitive temporal characteristics of sEMG signals to action amplitude and muscle recruitment patterns, an sEMG-based gesture recognition algorithm is innovatively proposed using Sigimg-GADF-MTF and multi-stream convolutional neural network (MSCNN) by introducing the Sigimg, GADF, and MTF data processing methods and combining them with a multi-stream fusion strategy. …”
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End-to-end neural automatic speech recognition system for low resource languages by Sami Dhahbi, Nasir Saleem, Sami Bourouis, Mouhebeddine Berrima, Elena Verdú

“…The rising popularity of end-to-end (E2E) automatic speech recognition (ASR) systems can be attributed to their ability to learn complex speech patterns directly from raw data, eliminating the need for intricate feature extraction pipelines and handcrafted language models. …”
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Neuropathic Pain Detection: An EEG-Based Brain Functional Network Approach by Abdulyekeen T. Adebisi, Ho-Won Lee, Kalyana C. Veluvolu

“…By extracting persistent homology features from these networks, we developed a support vector machine (SVM)-based classifier that distinguishes control subjects from those experiencing varying degrees of NP. …”
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Molecular and Clinical Overview of Type 1 Neurofibromatosis: Single Center Study and Mini Review on NF1-Associated Vasculopathy and Juvenile Myelomonocytic Leukemia by Şule Altıner, Alper Han Çebi

“…Molecular diagnosis is important in patients with an atypical presentation, as well as in children who have not yet developed sufficient characteristic features or for providing prenatal diagnosis. …”
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REVIEW OF: GOLUBKOVA O.N. FUNDAMENTALS OF SCIENTIFIC RESEARCH IN THE PROFESSIONAL FIELD: TEXTBOOK by A.A. Bilyalova, A.N. Utekhina

“…Patterns in the use of methodological concepts based on their functions in a study are highlighted. …”
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Leveraging machine learning for data-driven building energy rate prediction by Nasim Eslamirad, Mehdi Golamnia, Payam Sajadi, Francesco Pilla

“…Focusing on Dublin, we integrate diverse geospatial datasets with building-specific and neighbourhood-scale features to classify BER. Our approach leverages cutting-edge ML techniques, including Decision Trees (DT), Random Forest (RF), K-Nearest Neighbours (KNN), and Support Vector Machines (SVM), to develop highly accurate predictive models. …”
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The Reliability of Diagnosing Schizophrenia Using the GRU Layer in Conjunction with EEG Rhythms by Pankaj Kumar Sahu, Karan Jain

“…Deep learning methods and patterns found in EEG of brain activity are helpful features for verifying schizophrenia. …”
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Analysis of consumer purchase intentions using functional near-infrared spectroscopy(fNIRS): A neuromarketing study on the aesthetic packaging of Korean red ginseng products. by SuJin Bak, Jaeyoung Shin, Daeun Kim, Sungkean Kim

“…By measuring brain activities, we aim to develop neuromarketing techniques and provide insights into consumer purchasing decisions influenced by the aesthetic features of product packaging.…”
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Single-cell sequencing combined with machine learning to identify glioma biomarkers and therapeutic targets by Yu Yan, Zhengmin Chu, Qi Zhong, Genghuan Wang

“…A 16-gene DRG signature was developed for predicting the survival of glioma patients. …”
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Individualized spatial network predictions using Siamese convolutional neural networks: A resting-state fMRI study of over 11,000 unaffected individuals. by Reihaneh Hassanzadeh, Rogers F Silva, Anees Abrol, Mustafa Salman, Anna Bonkhoff, Yuhui Du, Zening Fu, Thomas DeRamus, Eswar Damaraju, Bradley Baker, Vince D Calhoun

“…Many neuroimaging studies have demonstrated the potential of functional network connectivity patterns estimated from resting functional magnetic resonance imaging (fMRI) to discriminate groups and predict information about individual subjects. …”
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A conceptual root zone model to calculate the application amount and frequency of water available for recharge by Francisco Flores-López, David Arrate, Mehrdad Bastani

“…The method is based on soil-land use combination, and crop saturation tolerance considering seasonal patterns during a long-term application of water available for recharge. …”
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Evaluation of K-Means Algorithm for Faulted Landforms Extraction and Offset Measurement With an Example From the Eastern Kunlun Fault by Shengchao Zhou, Zhou Lin

“…This study aims to develop a more objective and accurate method for identifying faulted landforms and measuring offsets. …”
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MODELING OF DEEP CURRENTS IN THE JAPAN SEA: RELATIONSHIP WITH THE CURRENTS IN THE THERMOCLINE LAYER by O. O. Trusenkova

“…Geostrophic deep circulation in the Japan Sea is modeled using the primitive equation multilayer model developed by N.B. Shapiro and E.M. Mikhaylova (Marine Hydrophysical Istitute, RAS). …”
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Machine learning based differential diagnosis of SAPHO syndrome and secondary bone tumors using whole body bone scintigraphy by Hongyang Jiang, Aihui Liu, Yihan Cao, Zhimin Lin, Haixu Jiang, Shengyan Liu, Qiuwei Peng, Xia Wu, Yuchen Liu, Xinbo Yu, Maming Wei, Yalin Pan, Chen Li, Zhenhua Ying

“…The WBBS findings of SAPHO syndromes and secondary bone tumors (SBT) have overlapping features, posing diagnostic challenges. In this multicenter study, we aim to identify different bone and joint involvement patterns between the two disease entities through multiple methods to build machine-learning models and explore interpretable variables. …”
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Rainfall-induced Landslide Susceptibility Prediction Considering Spatial Heterogeneity by ZHANG Xingfu, JIANG Yuanjun, ABI Erdi

“…Inputs such as terrain features, soil characteristics, vegetation indices, and rainfall patterns were utilized to train and evaluate the models. …”
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Fractal approach to geological and economic assessment of germanium-bearing lignites by O. I. Bilous, M. S. Burlutskyy

“…This article explores the development of scientifically robust methods for the geological and economic evaluation of germanium-bearing lignites, integrating geochemical, petrophysical, and economic considerations. …”
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Evaluation of the Occurrence of Initial Failures from Stress Concentrators in Welded Joints and Structural Elements by K. А. Molokov, V. V. Novikov, M. Dabalez

“…The literature on the topic was analyzed. The features of proven physical models and patterns of behavior of materials were taken into account. …”
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Evolution paths of urban forms influenced by landforms: Asynchrony but convergence by Chao Yang, Qiyan Huang, Qiong Xian, Meng Yuan, Xiaoming Cong, Lisha Xun, Jianxiong Cheng, Hongyi Pan

“…From 1990 to 2020, we quantitatively describe urban form characteristics using the two new indices alongside the landscape pattern index. Principal component analysis and hierarchical clustering are then employed to classify urban form types, revealing evolution patterns and trends across various landforms. …”
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Deep learning enabled integration of tumor microenvironment microbial profiles and host gene expressions for interpretable survival subtyping in diverse types of cancers by Haohong Zhang, Xinghao Xiong, Mingyue Cheng, Lei Ji, Kang Ning

“…In this study, we aimed to decode this complex relationship by developing ASD-cancer (autoencoder-based subtypes detector for cancer), a semi-supervised deep learning framework that could extract survival-related features from tumor microbiome and transcriptome data, and identify patients’ survival subtypes. …”
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