2.035 hasil untuk machine learning
Menampilkan 181–200 · 1,06 detik · RSS
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Innovative Learning Environments in STEM Higher Education
…opportunities, challenges, and future research initiatives of innovative learning environments (ILEs) in higher education STEM disciplines in their pioneering project: eXploring the Future of Innovative Learning Environments (X-FILEs). Workshop participants evaluated four main ILE categories…
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Application of Deep Learning in Underwater Image Processing
…traditional underwater image processing techniques. In recent years, deep learning technologies have emerged as a game-changer in addressing these challenges and improving underwater image quality. These technologies provide new opportunities and insights, enhancing their applicability and…
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Learning to Understand Remote Sensing Images
…the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book…
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AI in Learning: Designing the Future
AI (Artificial Intelligence) is predicted to radically change teaching and learning in both schools and industry causing radical disruption of work. AI can support well-being initiatives and lifelong learning but educational institutions and companies need to take the changing technology into…
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Information-Theoretic Methods in Deep Learning
The rapid development of deep learning has led to groundbreaking advancements across various fields, from computer vision to natural language processing and beyond. Information theory, as a mathematical foundation for understanding data representation, learning, and communication, has emerged as a…
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Machine Health Monitoring and Fault Diagnosis Techniques (Volume II)
…methods. The contributions encompass innovative approaches such as deep learning models for transformer and rolling bearing fault detection using vibration signals and time–frequency analyses, significantly boosting diagnostic accuracy and robustness. This collection also explores cutting-edge…
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Financial Data Analytics and Statistical Learning
Recently, there have been significant strides in the application of statistical learning techniques for solving financial, insurance, and various business and economic problems. These techniques, rooted in mathematical foundations and statistical theory and fueled by machine learning algorithms…
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Statistical Foundations of Actuarial Learning and its Applications
…such as generalized linear models, the book then dives into modern machine learning tools such as neural networks and text recognition to improve predictive modeling with complex features. Providing practitioners with detailed guidance on how to apply machine learning methods to real-world data…
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Deep Learning for Information Fusion and Pattern Recognition
…used for enhancing the performance of pattern classification, while deep learning (DL) technologies, including convolutional neural networks (CNNs), are powerful tools for improving object detection, segmentation, and recognition. It is viable to combine DL and IF to boost the overall performance…
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Advances in Computer Vision and Deep Learning and Its Applications
…and beyond. Up to now, image-processing technology based on deep learning has rapidly developed and become the most successful applied intelligent technology. Pattern recognition is an important research field in image processing and includes image preprocessing, feature extraction and selection…
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Reliability of Mechatronic Systems and Machine Elements: Testing and Validation
This reprint focuses on fundamental and applied research in the validation and testing of mechatronic systems and machine elements. It presents test strategies, reliability methods, and special insights into the systems under investigation. The focus is on advanced and complex mechatronic systems…
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Deep Learning Methods for Remote Sensing
…The recent impressive progress in artificial intelligence (AI) and deep learning has sparked innovations in technologies, algorithms, and approaches and led to results that were unachievable until recently in multiple areas, among them remote sensing. This book consists of sixteen peer-reviewed…
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Knowledge Modelling and Learning through Cognitive Networks
…recall patterns influence phenomena such as creativity, memory search, learning, and more generally, knowledge acquisition, exploration, and exploitation. In parallel, neural network models for artificial intelligence (AI) are also becoming more widespread as inferential models for understanding…
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Artificial Intelligence-Based Learning Approaches for Remote Sensing
The reprint focuses on artificial intelligence-based learning approaches and their applications in remote sensing fields. The explosive development of machine learning, deep learning approaches and its wide applications in signal processing have been witnessed in remote sensing. The new…
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Various Deep Learning Algorithms in Computational Intelligence
This reprint highlights the importance of Deep Learning (DL), which has garnered significant attention in science, industry, and academia. It draws inspiration from the functioning of the human brain and the concept of learning. Unlike traditional and machine learning methods, deep learning…
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Data Mining and Computational Intelligence for E-learning and Education
This Reprint, Data Mining and Computational Intelligence for E-learning and Education, presents a collection of cutting-edge research focused on the application of artificial intelligence to educational contexts. The selected contributions explore how data mining and intelligent algorithms can be…
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Test and Evaluation Methods for Human-Machine Interfaces of Automated Vehicles II
…new, standardized tests and evaluating methods for in-vehicle Human–Machine Interfaces (HMIs). This Special Issue includes theoretical papers as well as empirical studies that propose new and innovative test methods in the evaluation of ADS HMIs.
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Deep Learning in Image Processing and Pattern Recognition
…development of image processing, especially with the application of deep learning, enabling it to become the most successfully applied intelligent technology. Pattern recognition is an important research field in image processing and includes image preprocessing, feature extraction and selection…
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Individual differences in early instructed language learning
Variability in predispositions for language learning has attracted scholarly curiosity for over 100 years. Despite major changes in theoretical explanations and foreign/second language teaching paradigms, some patterns of associations between predispositions and learning outcomes seem timelessly…
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Review Papers in Big Data, Cloud-Based Data Analysis and Learning Systems
…used to solve Big Data problems and obtain valuable information and learning processes in a reasonable time. This Special Issue includes high-quality research papers in the fields of big data, cloud-based data analysis, and machine learning systems. In particular, wide-ranging surveys and advanced…
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