204.674 hasil untuk machine learning
Menampilkan 201–220 · 2,30 detik · RSS
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Artikel Jurnal
Applied machine learning for liver surgery
…we developed a new approach that implements cutting-edge research in machine learning and nevertheless is cheap and easily applicable in a routine clinical setting is needed. Methods: After splitting the study population into a training and test set we trained a convolutional neural network to…
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Artikel Jurnal
Machine learning plastic deformation of crystals
Predicting plastic deformation in crystals remains challenging owing to the nonlinear nature of stochastic avalanches involved, which resemble the critical phenomena. Salmenjoki et al. use machine learning to predict plastic deformation and show that it works better for those under large strains.
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Artikel Jurnal Teks lengkap
GEOLOGICAL MAPPING USING MACHINE LEARNING ALGORITHMS
…environmental monitoring and mineral exploration. Using these data with Machine Learning Algorithms (MLA), which are widely used in image analysis and statistical pattern recognition applications, may enhance preliminary geological mapping and interpretation. This approach contributes towards a…
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Artikel Jurnal Teks lengkap
Machine Learning Frameworks in Cancer Detection
…from the bioscience and genomics field to investigate the utilization of machine learning (ML) algorithms in cancer diagnosis and treatment. Because of this, these methods have been used with the goal of simulating the development and treatment of malignant diseases in humans. Furthermore, the…
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Artikel Jurnal
Machine Learning‐Enabled Smart Sensor Systems
Recent advancements and major breakthroughs in machine learning (ML) technologies in the past decade have made it possible to collect, analyze, and interpret an unprecedented amount of sensory information. A new era for “smart” sensor systems is emerging that changes the way that conventional…
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Artikel Jurnal
Blockchain meets machine learning: a survey
Abstract Blockchain and machine learning are two rapidly growing technologies that are increasingly being used in various industries. Blockchain technology provides a secure and transparent method for recording transactions, while machine learning enables data-driven decision-making by analyzing…
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Artikel Jurnal Teks lengkap
Monitoring Mushroom Growth with Machine Learning
…in the agriculture area. In this paper, we evaluate the effectiveness of machine learning for mushroom growth monitoring for the genus Pleurotus. We use YOLOv5 to detect mushrooms’ growing stage and indicate those ready to harvest. The results show that it can detect mushrooms in the greenhouse…
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Artikel Jurnal Teks lengkap
Quasar: Easy Machine Learning for Biospectroscopy
…to follow quickly changing, cutting-edge research demands. Finally, as machine learning techniques penetrate data analysis pipelines of the natural sciences, we see the growing demand for user-friendly and flexible tools to fuse machine learning with spectroscopy datasets. In our opinion…
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Artikel Jurnal Teks lengkap
Optimizing truss members using Machine Learning
This paper aims to produce an optimization methodology for a truss for minimal stress on critical sections using Machine learning models. This is done by varying the height and length of the truss span and applying live loads on different joints. The optimization of the truss is done through feed…
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Artikel Jurnal Teks lengkap
Sensors Data Processing Using Machine Learning
Various sensors utilize computational models to estimate measured variables, and the generated data require processing [...]
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Artikel Jurnal
Automated spectrometer alignment via machine learning
During beam time at a research facility, alignment and optimization of instrumentation, such as spectrometers, is a time-intensive task and often needs to be performed multiple times throughout the operation of an experiment. Despite the motorization of individual components, automated alignment…
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Artikel Jurnal
Machine Learning Empowered Software Prediction System
…measurements. Defects are determined using a variety of models. Using machine learning, the defect prediction model may be developed. Machine inclining in the second and third levels is dependent on the preparation and assessment of data (to break down model execution). Defect prediction models…
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Artikel Jurnal Teks lengkap
Refining fast simulation using machine learning
…in some of the final analysis observables. In this contribution, a machine learning-based technique to refine those observables is presented. We employ a regression neural network trained with a sophisticated combination of multiple loss functions to provide post-hoc corrections to samples produced…
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Artikel Jurnal Teks lengkap
Machine Learning in Quasi-Newton Methods
In this article, we consider the correction of metric matrices in quasi-Newton methods (QNM) from the perspective of machine learning theory. Based on training information for estimating the matrix of the second derivatives of a function, we formulate a quality functional and minimize it by using…
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Artikel Jurnal
Machine learning based energy demand prediction
…specified prediction baseline to be compared with. This paper proposes a machine learning (ML) based prediction framework that investigates how temperature combined with energy consumption and simple and interpretable ML methods can be used to provide more precise demand forecasts and thus…
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Artikel Jurnal
Rediscovering orbital mechanics with machine learning
We present an approach for using machine learning to automatically discover the governing equations and unknown properties (in this case, masses) of real physical systems from observations. We train a ‘graph neural network’ to simulate the dynamics of our Solar System’s Sun, planets, and large…
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Artikel Jurnal
Machine learning assisted vector atomic magnetometry
…a paradigm of indirect encoding for vector atomic magnetometry based on machine learning. We encode the three-dimensional magnetic-field information in the set of four simultaneously acquired signals associated with the optical rotation of a laser beam traversing the atomic sample. The map between…
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Artikel Jurnal
Machine learning mutation-acyclicity of quivers
Machine learning (ML) has emerged as a powerful tool in mathematical research in recent years. This paper applies ML techniques to the study of quivers—a type of directed multigraph with significant relevance in algebra, combinatorics, computer science, and mathematical physics. Specifically, we…
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