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• Applied Machine Learning for Predicting Crop Performance: A Supervised Learning Perspective
  Agriculture is fraught with uncertainty due to climate change, rainfall, soil types, and many other factors. Crop prediction in agriculture is a major dilemma and there are huge data sets where farmers struggle to predict the right seed. In this situation of p…
  crossref 2024-08-14T03:16:35Z 置信度 0.70
• Determinants of Bitcoin Price: A Machine Learning Approach
  crossref Levent Kutlu 2024-04-30T15:53:20Z 置信度 0.70
• Perceptron
  crossref Hang Li 2023-12-06T00:02:11Z 置信度 0.70
• Machine learning potential for serpentines
  Serpentines are layered hydrous magnesium silicates (MgO·SiO2·H2O) formed through serpentinization, a geochemical process that significantly alters the physical property of the mantle. They are hard to investigate experimentally and computationally due to the …
  crossref Hongjin Wang, Chenxing Luo, Renata Wentzcovitch 2024-09-26T15:36:13Z 置信度 0.70
• Innovative Strategies for Ensuring Privacy in Machine Learning Environments
  This paper presents an in-depth examination of privacy-enhancing methodologies in machine learning. It highlights the integration of federated learning with cutting-edge encryption techniques and explores how blockchain architectures contribute to data privacy…
  crossref Elham Shammar 2024-01-26T15:28:16Z 置信度 0.70
• Decision letter for "Quantum machine learning for image classification"
  crossref 2024-02-21T16:15:33Z 置信度 0.70
• Upscaling hydrologic phenomena using machine learning
  Hydrologic processes in snowmelt dominated systems are traditionally measured and understood at the point scale. However, snowmelt, sublimation, and snowfall rates exhibit significant spatial variability across larger landscapes. These variations are influence…
  crossref Hannah Burdett, James R Craig 2024-07-29T00:04:25Z 置信度 0.70
• Proceedings of the 2024 7th International Conference on Signal Processing and Machine Learning
  crossref 2024-10-11T16:29:37Z 置信度 0.70
• An Evaluation and Comparison of Machine Learning Methods for Prediction of Lubricant Film Thickness
  Lubricant film thickness is a tribological parameter that significantly impacts the performance of a tribo-system, primarily by affecting the resulting friction and wear. Measuring or predicting film thickness is therefore crucial for any hydrodynamically lubr…
  crossref Caleb Combs, Edgar Avalos Gauna, C. Fred Higgs 2025-03-04T18:39:11Z 置信度 0.70
• A Novel Mechanism for Identifying Malicious and Phishing URLs Using Machine Learning Classifiers
  Phishing attacks are a straightforward method for obtaining sensitive information from unsuspecting users. The goal of phishers is to acquire critical data such as usernames, passwords, and bank account details. The threat of network information insecurity is …
  crossref V. Lokeswara Reddy, M.V. Sai Sarath Chandra 2025-02-11T18:21:27Z 置信度 0.70
• Author Index
  crossref 2024-11-21T19:04:04Z 置信度 0.70
• Machine Learning-based Design and Optimization of High-Speed Circuits
  This book describes machine learning-based new principles, methods of design and optimization of high-speed integrated circuits.
  crossref Vazgen Melikyan 2023-12-30T10:02:41Z 置信度 0.70
• Organizing Committees
  crossref 2025-04-29T17:29:35Z 置信度 0.70
• Carbon Price Forecasting with Optimized Machine Learning Methods
  crossref Ozan Nadirgil 2024-07-16T10:22:21Z 置信度 0.70
• Contents
  crossref 2024-08-22T18:47:27Z 置信度 0.70
• Machine learning-based seismic prediction of building structures
  The impact of earthquakes on building structures is the most direct and significant aspect of earthquake disasters, and the seismic resistance of building structures is a key factor in ensuring human safety and reducing economic losses. Ground shaking caused b…
  crossref Shuai Liu, Hailiang Peng, Xiaolu Deng 2024-08-03T06:41:34Z 置信度 0.70
• Reviewers: FMLDS 2024
  crossref 2025-02-17T18:27:08Z 置信度 0.70
• Review for "Machine learning interatomic potentials for amorphous zeolitic imidazolate frameworks"
  crossref 2024-09-27T00:02:30Z 置信度 0.70
• Machine Learning Prediction of Lightning Damage to Aircraft
  Lightning can cause physical damage to the aircraft structure, including the wings, nose cone, and other components. This damage can compromise the structural integrity of the aircraft and pose a serious risk to passenger safety. In addition, it can cause elec…
  crossref Pavlo Kochkin 2024-03-11T12:43:31Z 置信度 0.70
• Information-Driven Machine Learning
  This textbook explains the 'why' behind data science, deep learning, and machine learning, and explores a systematic approach to model engineering
  crossref Gerald Friedland 2023-12-01T06:04:04Z 置信度 0.70
• 2024 IEEE 3rd Workshop on Machine Learning on Edge in Sensor Systems (SenSys-ML)
  crossref 2024-06-24T17:22:44Z 置信度 0.70
• ICBDML 2024 TOC
  crossref 2024-07-02T18:12:18Z 置信度 0.70
• Machine learning-assisted Fourier transform infrared and Raman spectroscopic sensing in agricultural and food systems
  crossref Tianjian Tong, Binbin Zhu, Chenxu Yu 2024-07-19T06:47:29Z 置信度 0.70
• Decision letter for "Quantum machine learning for image classification"
  crossref 2024-02-21T16:15:33Z 置信度 0.70
• Leveraging Machine Learning to Enhance Injury Prevention Strategies for Fast Bowlers
  Fast bowlers in cricket face a high risk of injury due to the immense physical strain associated with their role, often resulting in prolonged absences and performance declines. This study aims to develop a predictive model for fast bowler injuries using the R…
  crossref S Pandikumar, C Menaka, Arun M 2024-10-26T11:46:02Z 置信度 0.70
• Predicting College Admission Results with Machine Learning on Unstructured Online Data
  College admissions in the U nited States is a complex and often opaque process, leading to uncertainty and potential unfair biases. This paper presents a novel approach to predicting college admission results using machine learning on unstructured online data.…
  crossref John Tian, Yourui Shao 2025-02-17T18:27:08Z 置信度 0.70
• MLCAD 2024 Cover Page
  crossref 2024-11-06T18:37:40Z 置信度 0.70
• Rhythmische Vorteile in Big Data und Machine Learning
  Das Buch behandelt verschiedene Aspekte der Biophysik und die hierarchische Kommunikation zwischen verschiedenen biologischen Systemen.
  crossref 2025-01-29T05:35:35Z 置信度 0.70
• A Coherent Signal Detector Suitable for Machine Learning Applications
  Coherent signals, such as a time varying voltage appearing on a radio antenna, are fundamentally different than non-coherent signals, such as the power magnitude of an individual pixel in a CCD camera. This discussion explores the details of the differences be…
  crossref Charles Hansen 2024-10-21T14:15:40Z 置信度 0.70
• Review for "Machine learning interatomic potentials for amorphous zeolitic imidazolate frameworks"
  crossref 2024-09-27T00:02:30Z 置信度 0.70
• Strong Machine Learning: a Way Towards Human-Level Intelligence
  Machine learning has achieved remarkable success with deep learning technologies. However, these methods are often inefficient in terms of resources; they require large datasets, many parameters and consume much computational power. In this paper, I define a g…
  crossref Danko Nikolic 2024-01-02T05:25:27Z 置信度 0.70
• Choosing Features for Stress Prediction with Machine Learning
  Feature selection is a crucial step in building effective machine learning models, as it directly impacts model accuracy and interpretability.Driven by the aim of improving stress prediction models, this article evaluates multiple approaches for identifying th…
  crossref 2024-10-01T10:18:17Z 置信度 0.70
• Optimizing Renewable Energy Integration with Machine Learning for Sustainability
  Progressions in technologies for renewable energy have rendered feasible fresh avenues for energy production that is sustainable. Nonetheless, melding renewable energy sources into pre-existing power grids encounters hurdles, owing to their sporadic nature. Ma…
  crossref Ayaan Vijayakar 2024-08-02T16:32:43Z 置信度 0.70
• Testbed-19: Machine Learning Models Engineering Report
  crossref 2024-09-05T15:07:24Z 置信度 0.70
• Financial Applications of Machine Learning Using R Software
  In the last years, the financial sector has seen an increase in the use of machine learning models in banking and insurance contexts. Advanced analytic teams in the financial community are implementing these models regularly. In this paper, i present the diffe…
  crossref Sami Mestiri 2024-02-18T14:56:00Z 置信度 0.70
• A Comprehensive Review on Machine Learning and Transfer Learning Approaches in Liver Tumor Classification
  Using improvements in medical imaging technology like CT and MRI scans, liver tumor classification is essential for early detection and therapy planning. Nonetheless, there are several obstacles to overcome due to the variety of tumor features and the requirem…
  crossref Sheik Imran, Pradeep N 2024-07-25T12:10:31Z 置信度 0.70
• Clustering
  crossref Maria Deprez, Emma C. Robinson 2024-01-21T05:33:29Z 置信度 0.70
• Reinforcement Learning Paradigm
  crossref Wenmin Wang 2024-10-26T17:01:56Z 置信度 0.70
• Using machine learning to improve efficiency of acoustic nanogenerators
  Machine learning algorithms can effectively analyze data and identify key parameters for performance optimization.
  crossref Avery Thompson 2024-02-21T17:46:07Z 置信度 0.70
• Index
  crossref 2024-08-22T18:47:27Z 置信度 0.70
• The Re-Label Method For Data-Centric Machine Learning
  In industry deep learning application, our manually labeled data has a certain number of noisy data. To solve this problem and achieve more than 90 score in dev dataset, we present a simple method to find the noisy data and re-label the noisy data by human, gi…
  crossref Tong Guo 2024-12-02T17:50:56Z 置信度 0.70
• Review for "Machine learning interatomic potentials for amorphous zeolitic imidazolate frameworks"
  crossref 2024-09-27T00:02:30Z 置信度 0.70
• A Review of Cloud Security Solutions: Leveraging Machine Learning and Deep Learning Techniques
  As organizations continue to leverage the benefits of cloud computing, it is imperative to prioritize cloud security. A holistic approach that encompasses people, processes, and technologies is crucial for building a resilient cloud security posture. By stayin…
  crossref Dr. Priti Mishra 2024-02-22T12:09:01Z 置信度 0.70
• Reviewers
  crossref 2024-07-23T17:37:15Z 置信度 0.70
• Dirty Data Processing for Machine Learning
  This book offers valuable take-away suggestions on dirty data processing and model selection for machine learning tasks.
  crossref Zhixin Qi, Hongzhi Wang, Zejiao Dong 2023-11-29T11:32:46Z 置信度 0.70
• Machine Learning in Pituitary Surgery
  Machine learning applications in neurosurgery are increasingly reported for diverse tasks such as faster and more accurate preoperative diagnosis, enhanced lesion characterization, as well as surgical outcome, complications and healthcare cost prediction. Even…
  crossref Vittorio Stumpo, Victor E. Staartjes, Luca Regli, Carlo Serra 2021-12-03T21:02:48Z 置信度 0.70
• Network Type Recognition Using Machine Learning Techniques
  Abstract The telecom industry is going through a massive digital transformation with the adoption of ML, AI, feedback-based automation and advanced analytics to handle the next generation applications and services. AI concepts are not new; the algorithms used …
  crossref Debmalya Ray 2024-03-06T19:26:56Z 置信度 0.70
• Data Mining and Machine Learning with Applications
  The Special Issue entitled "Data Mining and Machine Learning with Applications aimed to connect researchers in the fields of deep learning, artificial intelligence, data mining, and machine learning. Included within this reprint are all the accepted articles t…
  crossref 2024-02-27T13:57:51Z 置信度 0.70
• Review for "MolToxPred: small molecule toxicity prediction using machine learning approach"
  crossref 2024-01-31T16:18:37Z 置信度 0.70
• Privacy Amplification in Quantum Key Distribution with Machine Learning
  The Quantum Key Distribution (QKD) method leverages the principles of quantum mechanics to securely create and distribute private keys using quantum systems and an authenticated public classical channel. Despite offering informationtheoretical security, its ph…
  crossref Nipun Agarwal 2024-07-15T15:40:41Z 置信度 0.70
• Proceedings of the 2024 2nd International Conference on Machine Learning and Pattern Recognition
  crossref 2024-12-17T04:58:59Z 置信度 0.70
• On BiasWrappers: New Regularization Techniques for Machine Learning Regression
  Regressive models in machine learning require regularization to balance the bias-variance tradeoff and attain realistic predictions in the real world. Two new regularization techniques, referenced as BiasWrappers, will be discussed in this paper: BiasWrapperC1…
  crossref Karthik Singaravadivelan 2024-02-12T09:00:21Z 置信度 0.70
• Gaze sequence enhanced with machine learning
  Gaze sequencing, the analysis of the order and duration of eye fixations, plays a crucial role in understanding human behavior, cognitive processes, and decision-making. It has applications in various fields such as human-computer interaction, healthcare, psyc…
  crossref Kelvin Jackson 2024-02-14T00:00:55Z 置信度 0.70
• Stock Market Prediction Using Machine Learning: Evidence from India
  crossref Subhamitra Patra, Trilok Nath Pandey, Biswabhusan Bhuyan 2024-08-26T22:02:03Z 置信度 0.70
• Title Page iii
  crossref 2024-05-10T17:22:05Z 置信度 0.70
• Linear threshold machines
  crossref Marco Gori, Alessandro Betti, Stefano Melacci 2023-06-05T05:21:34Z 置信度 0.70
• Classification
  crossref Carlos A. Escobar, Ruben Morales-Menendez 2024-03-22T09:07:52Z 置信度 0.70
• Answers to exercises
  crossref Marco Gori, Alessandro Betti, Stefano Melacci 2023-06-05T05:21:43Z 置信度 0.70
• Back Matter
  The back matter includes Bibliography, Index, and back cover.
  crossref 2024-04-11T18:47:43Z 置信度 0.70
• AI-Powered Anomaly Detection for Kubernetes Security: A Systematic Approach to Identifying Threats
  This study delves into the intricacies of AI-based threat detection in Kubernetes security, with a specific focus on its role in identifying anomalous behavior. By harnessing the power of AI algorithms, vast amounts of telemetry data generated by Kubernetes cl…
  crossref Arvind Kumar Bhardwaj, P.K. Dutta, Pradeep Chintale 2024-08-27T00:20:32Z 置信度 0.70
• Table of Contents
  crossref 2024-05-10T17:22:05Z 置信度 0.70
• Bank Customer Churn Prediction Using Machine Learning Framework
  crossref Rasha Ashraf 2024-03-13T10:18:50Z 置信度 0.70
• Fortifying Network Security with Machine Learning
  The pervasive integration of machine learning in various domains has positioned it at the forefront of technological advancements, with cybersecurity being a significant beneficiary. In this paper, we explore the widespread adoption of machine learning techniq…
  crossref Ashley Audrey Innocent Yanguema 2024-01-06T13:11:16Z 置信度 0.70
• Index
  crossref 2024-06-21T06:24:45Z 置信度 0.70
• Machine learning algorithms in personalized treatment planning
  Machine learning algorithms are revolutionizing personalized treatment planning by analyzing patient data to create tailored interventions. These algorithms optimize treatment strategies, improve outcomes, and minimize adverse effects, enabling precision medic…
  crossref Kiran Kumar Maguluri 2025-01-16T05:02:51Z 置信度 0.70
• Machine Learning Evaluation
  As machine learning applications gain widespread adoption and integration in a variety of applications, including safety and mission-critical systems, the need for robust evaluation methods grows more urgent. This book compiles scattered information on the top…
  crossref Nathalie Japkowicz, Zois Boukouvalas 2024-11-07T00:06:30Z 置信度 0.70
• Applications of artificial intelligence, machine learning, and deep learning in plant breeding
  crossref 2024-09-24T12:45:10Z 置信度 0.70
• Introduction
  crossref Carlos A. Escobar, Ruben Morales-Menendez 2024-03-22T09:07:43Z 置信度 0.70
• Authors
  crossref 2024-08-15T17:18:59Z 置信度 0.70
• The big picture
  crossref Marco Gori, Alessandro Betti, Stefano Melacci 2023-06-05T05:21:30Z 置信度 0.70
• Front Matter
  METAHEURISTICS for MACHINE LEARNING The book unlocks the power of nature-inspired optimization in machine learning and presents a comprehensive guide to cutting-edge algorithms, interdisciplinary insights, and real-world applications. The field of metaheuristi…
  crossref 2024-03-29T21:41:43Z 置信度 0.70
• Copyright Page
  crossref 2025-04-29T17:29:35Z 置信度 0.70
• Copyright
  crossref 2024-06-20T12:05:48Z 置信度 0.70
• Insights into Deep Learning and Non-Deep Learning Techniques for Code Clone Detection
  A source code clone is a type of bad smell caused by pieces of code that have the same functional semantics, but the syntactical representation varies. In the past few years, there have been several studies about code clone detection, steered by numerous machi…
  crossref Ajinkya Kunjir 2024-05-10T11:38:12Z 置信度 0.70
• Using machine learning to provide understanding along with results
  A cyclical implementation of machine learning algorithms provides insights into physical mechanisms, improving efficiency.
  crossref Avery Thompson 2024-08-09T12:39:50Z 置信度 0.70
• Early detection approach for analysis of osteoarthritis using artificial intelligence and machine learning
  crossref Chander Prabha 2024-11-22T05:37:30Z 置信度 0.70
• Frontmatter
  crossref 2024-08-22T18:47:27Z 置信度 0.70
• Galaxy Classification with Machine Learning
  Galaxy classification, a fundamental task in astronomy, involves categorizing galaxies based on their morphological features. To streamline this process and reduce manual effort, researchers have turned to machine learning methods. A recent study explored seve…
  crossref Abhinav Singh, Prashante ., Indra Kumari 2024-08-28T09:10:19Z 置信度 0.70
• Review for "Prediction of hydrogel swelling states using machine learning methods"
  crossref 2024-05-04T17:08:25Z 置信度 0.70
• Prediction of Neonatal Mortality from Jaundice Using Machine Learning
  Around the world, jaundice – a birth complication – is the primary cause of newborn mortality and morbidity. As more is discovered about the causes of this illness and possible therapies, the severity of the conditions may lessen. While some progress has been …
  crossref Mayank Srivastava, Yajur, Sujata 2024-11-22T14:16:12Z 置信度 0.70
• Development of a Machine Learning derived Anticholinergic Burden Scale (ML-ACB scale): A Machine Learning Approach with Enhanced Drug Properties and Weighting
  Aim: This study aims to refine the anticholinergic burden (AB) scale developed in our previous research by incorporating additional drug properties, such as Lipophilicity and Molecular Weight, and implementing a new weighting approach to address the varying in…
  crossref Oteng Phutietsile, Nikoletta Fotaki, Prasad Nishtala 2024-10-03T06:32:12Z 置信度 0.70
• Author comment: Machine learning for stochastic parametrization — R0/PR1
  Atmospheric models used for weather and climate prediction are traditionally formulated in a deterministic manner. In other words, given a particular state of the resolved scale variables, the most likely forcing from the subgrid scale processes is estimated a…
  crossref Hannah Christensen 2025-01-22T04:57:24Z 置信度 0.70
• Deep Learning Machine Vision
  Wie können industrielle Bildverarbeitung (IBV), 3D-Technologie und Robotik die Fertigungsprozesse und Lieferketten für Elektrobatterien unterstützen? Dies war im Juni 2024 auf der Branchenveranstaltung in Stuttgart zu sehen.
  crossref 2024-09-18T03:58:50Z 置信度 0.70
• Cover
  crossref 2024-11-04T18:31:55Z 置信度 0.70
• Preface
  crossref 2024-09-19T17:22:29Z 置信度 0.70
• Cover
  crossref 2024-12-20T18:56:07Z 置信度 0.70
• Internet of Things and Machine Learning for Type I and Type II Diabetes
  crossref 2024-07-19T06:25:56Z 置信度 0.70
• Breast Cancer Prediction Using a Machine Learning Approach
  Every year, millions of people are dying due to cancer. Cancer is a group of diseases that involves abnormal or out-of-control cell growth. The actual reason for this abnormal cell growth is still unknown. This abnormal cell growth can spread to other parts of…
  crossref Arijit Ghosal, Harshita Somolu, Suchibrota Dutta 2024-04-19T18:45:33Z 置信度 0.70
• Machine Learning—Automated Machine Learning (AutoML) for Disease Prediction
  crossref Jason H. Moore, Pedro H. Ribeiro, Nicholas Matsumoto, Anil K. Saini 2023-11-04T05:08:25Z 置信度 0.70
• Front Matter
  crossref 2024-05-24T10:12:21Z 置信度 0.70
• Proceedings
  crossref 2024-07-23T17:37:15Z 置信度 0.70
• Unsupervised Anomaly Detection
  This research focuses on Unsupervised Anomaly Detection using the "ambient_temperature_system_failure.csv" dataset from Numenta Anomaly Benchmark (NAB). The dataset contains time-series temperature readings from an industrial machine's sensor. The aim is to de…
  crossref Suliman Alnutefy, Ali Alsuwayh 2024-02-04T14:25:56Z 置信度 0.70
• Speaker identification using hybrid subspace, deep learning and machine learning classifiers
  Abstract Speaker identification is crucial in many application areas, such as automation, security, and user experience. This study examines the use of traditional classification algorithms and hybrid algorithms, as well as newly developed subspace classifiers…
  crossref Serkan KESER, Esra GEZER 2024-05-14T07:03:25Z 置信度 0.70
• Machine learning with sklearn
  This chapter’s goal is to show how to apply machine learning algorithms in a general setting using some classic methods. In particular, it demonstrates how to apply three important machine learning algorithms, a support vector classifier (SVC), a random forest…
  crossref Thomas P. Trappenberg 2020-01-23T10:54:18Z 置信度 0.70
• DDoS Detection using Machine Learning
  In the cybersecurity domain, Denial of Service (DoS) attacks maliciously disrupt the availability of systems, inundating them with packets or requests. Distributed Denial of Service (DDoS) attacks compound this challenge, utilizing multiple compromised sources…
  crossref Nour Ahmed Nagah, Mariam Bahaa, Wael Farouk Elsersy 2024-07-11T17:39:34Z 置信度 0.70
• Optimized Extreme Learning Machine with Bacterial Colony Optimization Algorithm for Disease Diagnosis in Clinical Datasets
  crossref P. Vigneshvaran, A. Vijaya Kathiravan 2024-05-26T17:01:17Z 置信度 0.70
• Clinical Applications of Machine Learning
  Objective: This review introduces interpretable predictive machine learning approaches, natural language processing, image recognition, and reinforcement learning methodologies to familiarize end users. Background: As machine learning, artificial intelligence,…
  crossref Nadayca Mateussi, Michael P. Rogers, Emily A. Grimsley, Meagan Read 等 2024-04-18T14:00:05Z 置信度 0.70
• Copyright Page
  crossref 2024-11-21T19:04:04Z 置信度 0.70
• Index
  crossref 2024-07-19T06:48:34Z 置信度 0.70
• Unveiling Diagnostic Precision: Evaluating Machine Learning and Deep Learning Approaches for Pneumonia Recognition of COVID-19 Patients Using Chest X-Rays
  crossref Nakiba Nuren Rahman, Rashik Rahman, Nusrat Jahan, Md. Akhtaruzzaman Adnan 2024-08-13T17:03:06Z 置信度 0.70