FRANet: A Feature Refinement Attention Network for SAR Image Denoising by Shuaiqi Liu, Yu Lei, Qi Hu, Ming Liu, Bing Li, Weiming Hu, Yu-Dong Zhang

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Personalised Affective Classification Through Enhanced EEG Signal Analysis by Joseph Barrowclough, Nonso Nnamoko, Ioannis Korkontzelos

“…This overlooks individual differences and may not accurately capture the unique emotional patterns of each person.Methods This study explored the performance of six machine learning algorithms in classifying a benchmark EEG dataset (collected with a MUSE device) for affective research. …”
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Massive unsourced multiple access scheme based on block sequence codebook and compressed sensing by Jing ZHANG, Lin MA, Chulong LIANG, Hongxu GAO

“…A massive unsourced multiple access scheme based on block sequence codebook and compressed sensing was proposed for sporadic burst scenario in massive machine type communication (mMTC).Firstly, a large-capacity spreading codebook generation scheme was designed according to a specific shift pattern, thus the codebook space was expanded.Secondly, the sparse structure of uplink signal was combined with multi-carrier technology to support overlapping transmission of multi-user data on some subcarriers, thus the spectral efficiency was improved.Finally, a multi-carrier CS-MUD model was established, and a group orthogonal matching pursuit algorithm based on codebook sequence blocks was designed to achieve the joint detection of active users and their uplink data.Simulation results show that the proposed scheme can effectively reduce the bit error rate of massive random access.…”
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QuantiFly: Robust Trainable Software for Automated Drosophila Egg Counting. by Dominic Waithe, Peter Rennert, Gabriel Brostow, Matthew D W Piper

“…The basis of the QuantiFly software is an algorithm which applies and improves upon an existing advanced pattern recognition and machine-learning routine. …”
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Improving cancer detection through computer-aided diagnosis: A comprehensive analysis of nonlinear and texture features in breast thermograms. by Hamed Khodadadi, Shima Nazem

“…Besides, to optimize feature selection and reduce redundancy, a metaheuristic optimization technique called Non-Dominated Sorting Genetic Algorithm (NSGA III) is applied. The proposed method utilizes various machine learning algorithms, including Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), Pattern recognition Network (Pat net), and Fitting neural Network (Fit net), for classification. ten-fold cross-validation ensures robust performance evaluation. …”
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Statistical and neural network assessment of the climatology of fog and mist at Pula Airport in Croatia by M. Zoldoš, M. Zoldoš, T. Džoić, J. Jurković, F. Matić, S. Jambrošić, I. Ljuština, M. Telišman Prtenjak

“…To identify weather patterns associated with the occurrence of fog and mist, wind and mean sea level pressure (MSLP) data from the fifth-generation reanalysis (ERA5) of the European Centre for Medium-Range Weather Forecasts (ECMWF) were analyzed using Growing Neural Gas (GNG), a machine learning algorithm. …”
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A Statistical Optimization Method for Sound Speed Profiles Inversion in the South China Sea Based on Acoustic Stability Pre-Clustering by Zixuan Zhang, Ke Qu, Zhanglong Li

“…Aiming at the problem of accuracy degradation caused by the mixing of spatiotemporal disturbance patterns in sound speed profile (SSP) inversion using the traditional geographic grid division method, this study proposes an acoustic stability pre-clustering framework that integrates principal component analysis and machine learning clustering. …”
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Identifying Public Transit Commuters Based on Both the Smartcard Data and Survey Data: A Case Study in Xiamen, China by Shichao Sun, Dongyuan Yang

“…Compared with existing methods which were plagued by the validation of the accuracy of the identification results, the adopted approach was a machine learning algorithm with functions of accuracy checking. …”
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Analisis Algoritma Klasifikasi Untuk Mengidentifikasi Potensi Risiko Kesehatan Ibu Hamil by Jajang Jaya Purnama, Nina Kurnia Hikmawati, Sri Rahayu

“…In this study the author identified potential maternal health risks for pregnant women by classifying them used machine learning which aims to analyze maternal health datasets with several algorithms including Random Forest, Extra Trees, Extreme Gradient Boosting, Decision Tree, and Light Gradient Boosting Machine. …”
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Identification of Perceptual Phonetic Training Gains in a Second Language Through Deep Learning by Georgios P. Georgiou

“…Deep learning enables the automatic extraction of complex patterns in learner behavior that might be missed by traditional methods. …”
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Forecasting Urban Sprawl Dynamics in Islamabad: A Neural Network Approach by Saddam Sarwar, Hafiz Usman Ahmed Khan, Falin Wu, Sarah Hasan, Muhammad Zohaib, Mahzabin Abbasi, Tianyang Hu

“…The artificial neural network (ANN) model embedded in IDRISI software 18.0v based on a well-defined backpropagation (BP) algorithm was used to simulate future urban sprawl considering the historical pattern for 2015–2020. …”
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Adaptation of k-means to automated forecasting of poorly structured time series of economic dynamics by Dunskaia Lada, Popova Elena

“…Data mining methods used in machine learning or deep learning allow to take into account complex patterns and nonlinear dependencies in the data. …”
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Discriminatively Constrained Semi-Supervised Multi-View Nonnegative Matrix Factorization with Graph Regularization by Guosheng Cui, Ye Li, Jianzhong Li, Jianping Fan

“…Nonnegative Matrix Factorization (NMF) is one of the most popular feature learning technologies in the field of machine learning and pattern recognition. It has been widely used and studied in the multi-view clustering tasks because of its effectiveness. …”
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Tree networks of real-world data: Analysis of efficiency and spatiotemporal scales by Davide Cipollini, Lambert Schomaker

“…Using an algorithm that creates and searches trees of real-world patterns, our work stands at the intersection of statistical physics, machine learning, and network theory. …”
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Enhancing MANET Security Through Federated Learning and Multiobjective Optimization: A Trust-Aware Routing Framework by Saad M. Hassan, Mohd Murtadha Mohamad, Farkhana Binti Muchtar, Firoz Bin Yusuf Patel Dawoodi

“…We evaluate this framework against existing protocols across various scenarios, including different network densities, mobility patterns, and malicious node percentages. Results demonstrate FLSTMT-LAR’s superior performance in high-threat environments, achieving up to 80% packet delivery ratio compared with 45% for traditional approaches. …”
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Examination of Teacher Candidates’ Intercultural Sensitivity Levels by CART Analysis by Nesrin Hark Söylemez

“…To predict intercultural sensitivity, five machine learning algorithms were utilized, with the Naive Bayes algorithm achieving the highest accuracy at 69.0%. …”
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A Spiking Neural Network With Adaptive Graph Convolution and LSTM for EEG-Based Brain-Computer Interfaces by Peiliang Gong, Pengpai Wang, Yueying Zhou, Daoqiang Zhang

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Optimized Identity Authentication via Channel State Information for Two-Factor User Verification in Information Systems by Chuangeng Tian, Fanjia Li, Xiaomeng Liu, Juanjuan Li

“…For classification, a kernel support vector machine (SVM) model is trained using a randomized hyperparameter search algorithm. …”
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Wavelet filterbank‐based EEG rhythm‐specific spatial features for covert speech classification by Sukanya Biswas, Rohit Sinha

“…With the motivation of deriving more discriminative features, each channel data has been decomposed into distinct bands focussing on the five basic EEG rhythms using the discrete wavelet transform (DWT)‐based signal decomposition algorithm. Following that, for each band, the multi‐class common spatial pattern (CSP) features are computed using joint approximate diagonalisation. …”
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Global intraspecific diversity of marine forests of brown macroalgae predicted by past climate conditions by Eliza Fragkopoulou, Ester A. Serrão, Olivier De Clerck, Jorge Assis

“…Here, we explain and predict the genetic diversity of cold and temperate brown macroalgae using genetic data from 29 species and a machine-learning algorithm that incorporates contemporary and past climate conditions during the Last Glacial Maximum (~20,000 years ago) based on the niche centroid hypothesis. …”
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