Klasifikasi Ulasan Palsu Menggunakan Borderline Over Sampling (BOS) dan Support Vector Machine (SVM) (Studi Kasus : Ulasan Tempat Makan) by Aisyah Awalina, Fitra Abdurrachman Bachtiar, Indriati Indriati

“…Ulasan palsu bisa secara efektif dibedakan menggunakan machine learning. Namun, banyak dari dataset ulasan palsu ini tidak seimbang (imbalanced dataset) sehingga dapat mempengaruhi hasil klasifikasi. …”
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Supply Capability Evaluation of Intelligent Manufacturing Enterprises Based on Improved BP Neural Network by Quan Quan, Zhongqiang Zhang

“…Based on the background of suppliers in intelligent manufacturing enterprises, the evaluation method of supplier efficiency was studied by using machine learning. In this paper, based on the traditional backpropagation (BP) neural network, combined with the improved particle swarm optimization (PSO) algorithm, and on the basis of the supplier evaluation index system, the supplier efficiency evaluation model of intelligent manufacturing enterprises based on DPMPSO-BP neural network is constructed. …”
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Practical Employment of Granular Computing to Complex Application Layer Cyberattack Detection by Rafał Kozik, Marek Pawlicki, Michał Choraś, Witold Pedrycz

“…Innovative approaches to handle this challenge are undertaken by the scientific community, proposing the utilization of the emerging, advanced machine learning methods. This very paper puts forward a novel approach to the detection of cyberattacks taking inventory of the practical application of information granules. …”
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Monocular Depth Estimation: A Review on Hybrid Architectures, Transformers and Addressing Adverse Weather Conditions by Kumara Lakindu, Senanayake Nipuna, Poravi Guhanathan

“…Monocular depth estimation has significantly improved over the past couple of years and deep learning-based methods have surpassed traditional and machine learning-based methods. Deep learning-based methods have further been enhanced using transformer and hybrid approaches. …”
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Recent Progress of Anomaly Detection by Xiaodan Xu, Huawen Liu, Minghai Yao

“…Anomaly analysis is of great interest to diverse fields, including data mining and machine learning, and plays a critical role in a wide range of applications, such as medical health, credit card fraud, and intrusion detection. …”
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Real-Time Football Match Prediction Platform by An Zhongqi

“…The platform employs machine learning models, including Random Forest, Support Vector Machines (SVM), and Neural Networks, combined with feature engineering techniques, to generate accurate predictions. …”
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Classification of diabetic retinopathy stages based on neural networks by M. M. Lukashevich, Y. I. Golub

“…Diabetic retinopathy can be detected much faster and more accurately by using machine learning methods for image analyzing of the human retina. …”
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The Power of Words: A Study of How Search Contents Can Affect Financial Decisions by Du Ni, Xingzhi Li, Zhi Xiao, Ke Gong

“…Therefore, this study was carried out to analyze the emotional meanings of 13,915 English words obtained from Google Trends and the profits gained from the US house market by automatic transactions and discovered that the emotional meanings of the search contents could modulate the financial decision with unsupervised machine learning methods.…”
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Lighting the way forward: The bright future of photonic integrated circuits by M.A. Butt, B. Janaszek, R. Piramidowicz

“…Its synergy with quantum information and machine learning opens innovation pathways. This review explores recent advancements in optical platforms, highlighting ongoing research and developments that are driving technological progress in this field. …”
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Financial Data Anomaly Detection Method Based on Decision Tree and Random Forest Algorithm by Qingyang Zhang

“…With the emergence of machine learning and data mining in recent years, new ideas and methods have emerged in the detection of abnormal network flows. …”
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Revolutionizing colorectal cancer detection: A breakthrough in microbiome data analysis. by Mwenge Mulenga, Arutchelvan Rajamanikam, Suresh Kumar, Saharuddin Bin Muhammad, Subha Bhassu, Chandramathi Samudid, Aznul Qalid Md Sabri, Manjeevan Seera, Christopher Ifeanyi Eke

“…However, the inherent high dimensionality, noise, and variability of microbiome data present substantial obstacles to conventional statistical methods and machine learning techniques. Even the promising deep learning (DL) methods are not immune to these challenges. …”
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Classifying the CP properties of the ggH coupling in H + 2j production by Henning Bahl, Elina Fuchs, Marc Hannig, Marco Menen

“…To improve the constraints on the $\mathcal{CP}$ structure of this coupling, we investigate Higgs production with two jets using machine learning. In particular, we exploit the $\mathcal{CP}$ sensitivity of the so far neglected phase space region that differs from the typical vector boson fusion-like kinematics. …”
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The Recognition of Holy Qur’an Reciters Using the MFCCs’ Technique and Deep Learning by Ghassan Samara, Essam Al-Daoud, Nael Swerki, Dalia Alzu’bi

“…We compare our proposed model to different deep learning and machine learning methodologies. Our proposed model outperformed the competing models with an accuracy of 99.66%, compared to the support vector machine’s accuracy of 99%.…”
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Preparing Schrödinger Cat States in a Microwave Cavity Using a Neural Network by Hector Hutin, Pavlo Bilous, Chengzhi Ye, Sepideh Abdollahi, Loris Cros, Tom Dvir, Tirth Shah, Yonatan Cohen, Audrey Bienfait, Florian Marquardt, Benjamin Huard

“…Scaling up quantum computing devices requires solving ever more complex quantum control tasks. Machine learning has been proposed as a promising approach to tackle the resulting challenges. …”
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Comparing ChatGPT And LSTM In Predicting Changes In Quarterly Financial Metrics by Vitali Chaiko

“…In recent years, machine learning has emerged as a powerful tool for such predictions. …”
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From pixels to prognosis: radiomics and AI in Alzheimer’s disease management by Danting Peng, Weiju Huang, Ren Liu, Wenlong Zhong

“…Recent advancements in radiomics and artificial intelligence (AI) offer novel solutions by integrating quantitative imaging features and machine learning algorithms to enhance diagnostic and prognostic precision. …”
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Quantum tug of war between randomness and symmetries on homogeneous spaces by Rahul Arvind, Kishor Bharti, Jun Yong Khoo, Dax Enshan Koh, Jian Feng Kong

“…Finally, as a practical demonstration of our findings, we study the expressibility of quantum machine learning Ansätze in homogeneous spaces. Our work provides a fresh perspective on the relationship between randomness and symmetry in the quantum world.…”
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Research on Modern Book Packaging Design under Aesthetic Evaluation Based on Deep Learning Model by Yuanyuan Li

“…To this end, this paper introduces the machine learning algorithms used in this paper, including the AdaBoost algorithm and the SVR algorithm. …”
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Improved Double-Layer Structure Multilabel Classification Model via Optimal Sequence and Attention Mechanism by Geqiao Liu, Mingjie Tan

“…Multilabel classification is a key research topic in the machine learning field. In this study, the author put forward a two/two-layer chain classification algorithm with optimal sequence based on the attention mechanism. …”
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PENERAPAN ARTIFICIAL INTELLIGENCE (AI) DALAM PERAMALAN AKUNTANSI TINJAUAN LITERATUR DAN AGENDA PENELITIAN MASA DEPAN by Gilang Surya Pratama, Agus Munandar

“…The analysis results show significant improvements in forecasting accuracy using AI technology, with Machine Learning achieving 78% accuracy in revenue forecasting, Deep Learning 85% in financial trend prediction, and Natural Language Processing 89% in sentiment analysis. …”
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