Prediction of Auditory Performance in Cochlear Implants Using Machine Learning Methods: A Systematic Review by Beyza Demirtaş Yılmaz

“…Study design, machine learning algorithms, and audiological measurements were evaluated in the data analysis. …”
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Dataset of apples for grading by sweetness, ripeness and varietyMendeley Data by Shilpa Gaikwad, Sonali Kothari, Ignisha Rajathi G

“…The resulting annotated database includes such quantitative reference points, which can be used to train supervised learning classifiers in computational classification systems.The reuse value of the dataset covers a wide range of applications such as machine learning-based fruit quality evaluation, agricultural automation and food industry examination. …”
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QoS-Aware Fault Detection in Wireless Sensor Networks by Alessandra De Paola, Giuseppe Lo Re, Fabrizio Milazzo, Marco Ortolani

“…The experimental evaluation produced good results, showing that our algorithm is able to greatly reduce the response time at the cost of a small reduction in classification accuracy.…”
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Semantic Segmentation-Driven Knowledge Distillation-Based Infrared Visible Image Fusion Framework by Xingshuo Wang

“…However, many existing fusion algorithms overly emphasize visual quality and traditional statistical evaluation metrics while neglecting the requirements of real-world applications, especially in high-level vision tasks. …”
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Fishing for biomarkers: analyzing mass spectrometry data with the new ClinProTools™ software by Ralf Ketterlinus, Sen-Yung Hsieh, Shih-Hua Teng, Helen Lee, Wolfgang Pusch

“…For this purpose, efficient visualization of large data sets derived from patient cohorts is crucial to provide clinical experts an interactive impression of the data quality. Additionally, it is necessary to apply statistical analysis and pattern matching algorithms to attain validated signal patterns that may allow for later applications in sample classification. …”
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A Summary of Recent Advances in the Literature on Machine Learning Techniques for Remote Sensing of Groundwater Dependent Ecosystems (GDEs) from Space by Chantel Nthabiseng Chiloane, Timothy Dube, Mbulisi Sibanda, Tatenda Dalu, Cletah Shoko

“…It begins with a systematic literature review following the PRISMA framework, followed by an analysis of temporal and geographic trends in ML applications for GDE research. Additionally, it explores different advanced ML algorithms and their applications across various GDE types. …”
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SCHEDULING PROBLEMS OF STATIONARY OBJECTS WITH THE PROCESSOR IN ONE-DIMENSIONAL ZONE by N. A. Dunichkina, D. I. Kogan, Yu. S. Fedosenko

“…Correspondingly, the bicriteria problem with the mentioned evaluation criteria is fundamentally intractable, computational complexity of the schedule structure algorithm is exponential. …”
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A survey on key technologies of privacy protection for machine learning by Zishan LIU, Qiang CHENG, Bo LV

“…With the development of information and communication technology,large-scale data collection has vastly promoted the application of machine learning in various fields.However,the data involved in machine learning often contains a lot of personal private information,which makes privacy protection face new risks and challenges,and has attracted more and more attention.The current progress of the related laws,regulations and standards to the personal privacy protection and data safety in machine learning were summarized.The existing work on privacy protection for machine learning was presented in detail.Privacy protection algorithms usually have influence on the data quality,model performance and communication cost.Thus,the performance of the privacy protection algorithms should be comprehensively evaluated in multiple dimensions.The performance evaluation metrics for the privacy protection algorithms for machine learning were presented,given with the conclusion that the privacy preservation on machine learning needs to balance the data quality,model convergence rate and communication cost.…”
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Active Inference-Driven Multi-Armed Bandits: Superior Performance through Dynamic Correlation Adjustments by Lin Xiaoqi

“…In recent years, Multi-Armed Bandit (MAB) algorithms have gained substantial attention due to their effectiveness in real-world applications, such as recommendation systems, autonomous systems, and dynamic resource allocation. …”
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Machine Learning Approaches for Software Defect Prediction by Hijab Zehra Zaidi, Ubaid Ullah, Muddassira Arshad, Hanan Aljuaid, Muhammad Arslan Rauf, Nadeem Sarwar, Rimsha Sajid

“…This paper analyses existing research about machine learning approaches in software defect prediction as a key element for improving software reliability and quality. The paper reviews the use of machine learning algorithms in software defect prediction framework’s bug prediction while assessing their performance across multiple environments. …”
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Analysis of disease severity and mortality prediction using machine learning during COVID-19 by Hodjat (Hojatollah) Hamidi, Mostafa Moradi

“…This paper focuses on how machine learning (ML) algorithms and applications have been used to analyze disease severity and mortality prediction in COVID-19 research. …”
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DEEP LEARNING-BASED SUPER-RESOLUTION TECHNIQUES: A COMPARATIVE ANALYSIS WITH RECENT INSIGHTS by Renuka Sambhaji Sindge, Maitreyee Dutta, Jagriti Saini

“…Current researchers have employed machine-learning techniques, neural networks, and Deep Learning based methods to enhance the quality of LR images obtained from different field applications. …”
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Framelet transform based edge detection for straight line detection from remote sensing images by Vidhya Rangasamy, Sulochana Subramaniam

“…Rosenfeld evaluation metric is used to measure the quality of the edge detection methods, which shows the framelet based edge detection produce sound results than other methods. …”
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Artificial intelligence-based automated breast ultrasound radiomics for breast tumor diagnosis and treatment: a narrative review by Yinglin Guo, Ning Li, Chonghui Song, Juan Yang, Yinglan Quan, Hongjiang Zhang

“…Radiomics, an emerging field, focuses on extracting high-dimensional quantitative features from medical imaging data and utilizing them to construct predictive models for disease diagnosis, prognosis, and treatment evaluation. In recent years, the integration of artificial intelligence (AI) with radiomics has significantly enhanced the process of analyzing and extracting meaningful features from large and complex radiomic datasets through the application of machine learning (ML) and deep learning (DL) algorithms. …”
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Nonreference Medical Image Edge Map Measure by Karen Panetta, Chen Gao, Sos Agaian, Shahan Nercessian

“…It is widely used to extract features, perform segmentation, and further assist in diagnosis. A poor quality edge map can result in false alarms and misses in cancer detection algorithms. …”
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Novel validity indices for dynamic clustering and an Improved Dynamic Fuzzy C-Means by Ramiro Saltos, Ignacio Carvajal, Fernando Crespo, Richard Weber

“…However, unlike static clustering, where a plethora of validation indices exist to assess the solution’s quality, evaluating the effectiveness of dynamic clustering algorithms remains a challenge. …”
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Artificial intelligence driven innovations in biochemistry: A review of emerging research frontiers by Mohammed Abdul Lateef Junaid

“…The methodology involves an extensive analysis of existing literature, particularly peer-reviewed studies on AI applications in biochemistry. AI-driven tools like AlphaFold, which have significantly advanced protein structure prediction, are evaluated alongside AI’s role in expediting drug discovery. …”
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Accuracy measurement of automatic remeshing tools by Mattia Sullini

“…<br />Therefore, it is vital to evaluate the characteristic quality obtainable from different remeshing algorithms with simplification, but despite the importance of the matter, there is a lack of metrics to perform such comparative benchmarks. …”
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Reliable Graph Routing in Industrial Wireless Sensor Networks by Jing Zhao, Yajuan Qin, Dong Yang, Junqi Duan

“…Our design is evaluated using simulation where we show that our algorithm could achieve a balance between routing reliability and overhead.…”
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Adaptation of mathematical educational content in e-learning resources by Yuliya V. Vainshtein, Victoria A. Shershneva, Roman V. Esin, Tatyana V. Zykova

“…An upcoming trend in improvement the quality of studying mathematical disciplines is the development and application of adaptive electronic educational resources. …”
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