204.674 hasil untuk machine learning
Menampilkan 781–800 · 1,03 detik · RSS
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Artikel Jurnal
Differential fault location identification by machine learning
…can be devised in the long run. In this regard, we propose a machine learning (ML) assisted tool that can be used in the context of a differential fault attack. In particular, finding the exact fault location by analysing the output difference (typically the XOR of the nonfaulty and the faulty…
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Artikel Jurnal
Quark-gluon tagging: Machine learning vs detector
Distinguishing quarks from gluons based on low-level detector output is one of the most challenging applications of multi-variate and machine learning techniques at the LHC. We first show the performance of our 4-vector-based LoLa tagger without and after considering detector effects. We then…
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Artikel Jurnal
Machine learning predictivity applied to consumer creditworthiness
…models using a Brazilian bank’s loan database, and exploring machine learning techniques. We develop Support Vector Machine, Decision Trees, Bagging, AdaBoost and Random Forest models, and compare their predictive accuracy with a benchmark based on a Logistic Regression model. Comparisons are…
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Artikel Jurnal
Quantum Embedding Search for Quantum Machine Learning
This paper introduces an automated search algorithm (QES, pronounced as “quest”), which derives optimal design of entangling layout for supervised quantum machine learning. First, we establish the connection between the structures of entanglement using CNOT gates and the representations of directed…
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Artikel Jurnal
Forecasting Corn Yield With Machine Learning Ensembles
…to more accurately predict crop yields. Recent research has shown that machine learning (ML) can provide reasonable predictions faster and with higher flexibility compared to simulation crop modeling. However, a single machine learning model can be outperformed by a “committee” of models (machine…
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Artikel Jurnal
Automated Machine Learning for COVID-19 Forecasting
In the context of the current COVID-19 pandemic, various sophisticated epidemic and machine learning models have been used for forecasting. These models, however, rely on carefully selected architectures and detailed data that is often only available for specific regions. Automated machine learning…
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Artikel Jurnal
Machine Learning in Orthopedics: A Literature Review
In this paper we present the findings of a systematic literature review covering the articles published in the last two decades in which the authors described the application of a machine learning technique and method to an orthopedic problem or purpose. By searching both in the Scopus and Medline…
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Artikel Jurnal
Machine Learning Prediction of Human Activity Recognition
…architecture for HAR systems are presented. HAR systems made use of machine learning techniques and tools, which are helpful to build patterns to describe, analyze, and predict data. Since a human activity recognition system should return a label such as walking, sitting, running, etc., most HAR…
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Artikel Jurnal
Machine learning in nephrology: scratching the surface
Abstract. Machine learning shows enormous potential in facilitating decision-making regarding kidney diseases. With the development of data preservation and processing, as well as the advancement of machine learning algorithms, machine learning is expected to make remarkable breakthroughs in…
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Artikel Jurnal
Machine-learning-based diagnostics of EEG pathology
Machine learning (ML) methods have the potential to automate clinical EEG analysis. They can be categorized into feature-based (with handcrafted features), and end-to-end approaches (with learned features). Previous studies on EEG pathology decoding have typically analyzed a limited number of…
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Artikel Jurnal
Objectification of intracochlear electrocochleography using machine learning
…different methods: correlation analysis, Hotelling's T2 test, and deep learning. We benchmarked these methods against the visual analysis of three ECochG experts.ResultsFor the visual analysis of ECochG recordings, the Fleiss' kappa value demonstrated a substantial to almost perfect agreement among…
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Artikel Jurnal
Finding New Perovskite Halides via Machine learning
…an efficient approach towards rational design of new materials, via learning from known data to make decisions on new and previously unexplored compounds in an accelerated manner. Here, we demonstrate the power and utility of such statistical learning (or machine learning) via building a support…
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Artikel Jurnal
Machine Learning Approach for Solar Wind Categorization
…events. With rapid developments in the field of artificial intelligence, machine learning approaches are increasingly being used for pattern recognition. In this study, an approach from machine learning perspectives is developed to automatically classify the solar wind at 1 AU into four types…
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Artikel Jurnal
Machine learning guided aptamer refinement and discovery
Current aptamer discovery approaches are unable to probe the complete space of possible sequences. Here, the authors use machine learning to facilitate the development of DNA aptamers with improved binding affinities, and truncate them without significantly compromising binding affinity.
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Artikel Jurnal
Machine Learning Magnetic Parameters from Spin Configurations
…a protocol for Hamiltonian parameters estimation from images based on a machine learning (ML) architecture is provided. It consists in learning a mapping between spin configurations and Hamiltonian parameters from a small amount of simulated images, applying the trained ML model to a single…
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Artikel Jurnal
Sherpa: Robust hyperparameter optimization for machine learning
Sherpa is a hyperparameter optimization library for machine learning models. It is specifically designed for problems with computationally expensive, iterative function evaluations, such as the hyperparameter tuning of deep neural networks. With Sherpa, scientists can quickly optimize…
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Artikel Jurnal
Application of machine learning in bacteriophage research
…the newly identified bacteriophages is inevitable for future research. Machine learning includes powerful techniques that enable the analysis of complex datasets for knowledge discovery and pattern recognition. In this study, we have conducted a comprehensive review of machine learning methods…
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Artikel Jurnal Teks lengkap
MACHINE LEARNING FOR SOYBEAN SEEDS LOTS CLASSIFICATION
…the physiological quality of soybean seeds in different cultivars using machine learning techniques to rank the lots based on their quality. Three cultivars were used, and the analysis was germination, accelerated aging, tetrazolium treatment, seedling emergence, and 1000 seed weight from 65 lots…
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Artikel Jurnal
Principles and Practice of Explainable Machine Learning
…trust them? In this report, we focus specifically on data-driven methods—machine learning (ML) and pattern recognition models in particular—so as to survey and distill the results and observations from the literature. The purpose of this report can be especially appreciated by noting that ML models…
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