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

“…Affective classification, which employs machine learning on brain signals captured from electroencephalogram (EEG), is a prevalent approach to address this issue. …”
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Prostate Cancer Detection from MRI Using Efficient Feature Extraction with Transfer Learning by Rafiqul Islam, Al Imran, Md. Fazle Rabbi

“…This research study investigates the utilization of machine learning techniques to diagnose prostate cancer. …”
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Skeleton-Based Data Augmentation for Sign Language Recognition Using Adversarial Learning by Yuriya Nakamura, Lei Jing

“…The generator produces hard adversarial data intended to mislead the machine learning model, which acts as a discriminator. …”
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Optimized Naive-Bayes and Decision Tree Approaches for fMRI Smoking Cessation Classification by Amirhessam Tahmassebi, Amir H. Gandomi, Mieke H. J. Schulte, Anna E. Goudriaan, Simon Y. Foo, Anke Meyer-Baese

“…The scientific research goal of this study was to interpret the fMRI connectivity maps based on machine learning algorithms to predict the patient who will relapse and the one who will not. …”
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Similarity Learning and Generalization with Limited Data: A Reservoir Computing Approach by Sanjukta Krishnagopal, Yiannis Aloimonos, Michelle Girvan

“…We investigate the ways in which a machine learning architecture known as Reservoir Computing learns concepts such as “similar” and “different” and other relationships between image pairs and generalizes these concepts to previously unseen classes of data. …”
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Improving the Accuracy for Analyzing Heart Diseases Prediction Based on the Ensemble Method by Xiao-Yan Gao, Abdelmegeid Amin Ali, Hassan Shaban Hassan, Eman M. Anwar

“…Heart disease is the deadliest disease and one of leading causes of death worldwide. Machine learning is playing an essential role in the medical side. …”
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Generating unseen diseases patient data using ontology enhanced generative adversarial networks by Chang Sun, Michel Dumontier

“…The quality of the generated data is evaluated using variable distributions, correlation coefficients, and machine learning model performance. Our findings demonstrate that Onto-CGAN generates unseen diseases with statistical characteristics comparable to the real data, and significantly improves the training of machine learning models. …”
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Face Recognition using Deep Learning and TensorFlow framework by Makrem Beldi

“…However, machine learning remains a relatively complex field that could feel intimidating or inaccessible to many of us. …”
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A convolutional neural network model and algorithm driven prototype for sustainable tilling and fertilizer optimization by Sajeev Magesh

“…This machine learning output, along with soil sensor and external forecast data, flows into a 10-parameter algorithm that determines optimal tilling and fertilizer levels. …”
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Option Volatility Investment Strategy: The Combination of Neural Network and Classical Volatility Prediction Model by Yuanyang Teng, Yicun Li, Xiaobo Wu

“…By investigating the traditional Volatility Prediction Model and machine learning algorithms, this study tries to merge these two aspects together. …”
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Developing an IoT and ML-driven platform for fruit ripeness evaluation and spoilage detection: A case study on bananas by Rajini M, Persis Voola

“…This study presents a novel framework that merges Internet of Things (IoT) and machine learning (ML) technologies to detect fruit ripeness and spoilage, which is essential in minimizing losses in the cold chain process of fresh produce industry. …”
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A TensorFlow implementation of Local Binary Patterns Transform by Devrim Akgün

“…Feature extraction layers like Local Binary Patterns (LBP) transform can be very useful for improving the accuracy of machine learning and deep learning models depending on the problem type. …”
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Dynamic Projection Mapping with a Single IR Camera by Naoki Hashimoto, Ryo Koizumi, Daisuke Kobayashi

“…We propose a dynamic projection mapping system with effective machine-learning and high-speed edge-based object tracking using a single IR camera. …”
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FAACOSE: A Fast Adaptive Ant Colony Optimization Algorithm for Detecting SNP Epistasis by Lin Yuan, Chang-An Yuan, De-Shuang Huang

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Long Short-Term Memory Recurrent Neural Network for Predicting the Return of Rate Underframe the Fama-French 5 Factor by Bui Thanh Khoa, Tran Trong Huynh

“…This study applied a machine learning technique to compare the performance of the Fama-French 5-factor model (FF5). …”
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Analisis Kredit Pembayaran Biaya Kuliah Dengan Pendekatan Pembelajaran Mesin by Arliyanti Nurdin, Rizqa Amelia Zunaidi, Muhammad Arkan Fauzan Wicaksono, Agi Lobita Japtara Martadinata

“…Pada penelitian ini, algoritma machine learning digunakan untuk analisis kredit pembayaran biaya kuliah pada perguruan tinggi. …”
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Multimodal Deep Learning for Differentiating Bacterial and Fungal Keratitis Using Prospective Representative Data by N.V. Prajna, MD, Jad Assaf, MD, Nisha R. Acharya, MD, MS, Jennifer Rose-Nussbaumer, MD, Thomas M. Lietman, MD, J. Peter Campbell, MD, MPH, Jeremy D. Keenan, MD, MPH, Xubo Song, PhD, Travis K. Redd, MD, MPH

“…Design: Machine learning classifier training and validation study. …”
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Enhancing Sentiment Analysis with a CNN-Stacked LSTM Hybrid Model by Shao Shuaijie

“…The performance of the model can be further improved, offering valuable insights for future hybrid model development in machine learning tasks.…”
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Diabetes Risk Assessment: A Comparative Study of Decision Trees and Ensemble Learning Models by Lei Tianxing

“…This high accuracy highlights the effectiveness of machine learning algorithms in predicting diabetes risk. …”
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Bulk Handling Facility Modeling and Simulation for Safeguards Analysis by Benjamin B. Cipiti, Nathan Shoman

“…This paper will describe the SSPM and its use for applying both traditional nuclear material accountancy and newer machine learning options.…”
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