边缘智能 · 全部实体（第 35 / 100 页）

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• Parametric Analysis, Generative Design and Machine Learning in Architectural Practice
  crossref Victor Okhoya, Marcelo Bernal 2026-06-26T23:12:41Z 置信度 0.70
• Machine learning in industrial cyberthreat detection
  crossref Mateusz PRANIUK 2026-02-20T12:35:36Z 置信度 0.70
• LaghuVani: How Clearly Can Tiny Vocoders Speak Bengali and Maithili?
  crossref Kaustubh S. Wade, Ravindrakumar M. Purohit, Hemant A. Patil 2026-04-20T11:48:00Z 置信度 0.70
• Innovation in Computer Science Learning Through Artificial Intelligence and Machine Learning Technologies
  <span>This conceptual paper proposes a novel framework for integrating artificial intelligence (AI) and machine learning (ML) technologies to innovate computer science education. The study employs a systematic literature review methodology, synthesizing …
  crossref Yulianto Tomi, Eri Kristiono, Nada Ratković, Tonia Sharlach 2026-08-22T07:40:11Z 置信度 0.70
• Customer Churn Prediction in E-Commerce Using Machine Learning and Deep Learning Techniques
  crossref Pratik Shantaram Wagaskar, Usha Shete 2026-05-19T07:17:11Z 置信度 0.70
• Self-supervised learning for pathological speech detection
  crossref Shakeel A. Sheikh 2026-04-23T14:57:11Z 置信度 0.70
• Unsupervised Machine Learning for Modelling Human Cognitive States in Learning Environments
  Abstract Understanding learner behaviour in digital environments is essential for developing adaptive educational systems. While prior research has largely focused on predictive modelling, less attention has been given to uncovering latent behavioural structur…
  crossref Patrick O. Akinwumi, Meihua Qian, Oyinkansola A. Babatope 2026-06-01T11:56:21Z 置信度 0.70
• Tiny Climbers
  crossref Elizabeth Anne Brown 2026-05-19T10:00:20Z 置信度 0.70
• An Explained Machine Learning Model for Analyzing Electric Vehicle Cyber Attacks
  crossref Amal Saif, Eman Alnagi, Ashraf Ahmad 2026-06-02T20:03:16Z 置信度 0.70
• Enhancing 3D Soil Characterization through Machine Learning from CPT Data
  crossref Laith Sadik, Sara Khoshnevisan 2026-03-05T14:48:03Z 置信度 0.70
• Uncertainty Quantification of Machine Learning Models With Adaptive Sampling Applications
  crossref Arjun Shah, Juan Alonso 2026-01-29T10:19:56Z 置信度 0.70
• Analyzing Adversarial Attacks on Federated Learning based Medical Image Classification
  crossref Soomaiya Hamid, Narmeen Zakaria Bawany 2026-05-21T19:40:47Z 置信度 0.70
• Fuzzy pre-extracting method for support vector machine
  crossref Chun-Hong Zheng, Li-Cheng Jiao 2003-06-25T21:03:42Z 置信度 0.70
• Detecting Operator Distraction Through Multivariate Signal Processing: Statistical and Machine Learning Perspectives
  crossref Mihai Constantinov, Daan M. Pool, Max Mulder 2026-07-15T20:02:01Z 置信度 0.70
• Weak Physics‐Guided Multi‐Agent Learning for Surface to Subsurface Moisture Estimation Across Diverse Climate and Soil Conditions
  Abstract Estimating subsurface soil moisture remains challenging due to limited in situ observations and the complexity of soil water dynamics. Although surface soil moisture can be retrieved from satellites with high accuracy, deeper layers are not directly o…
  crossref Abhilash Singh, Vidhi Singh, Kumar Gaurav 2026-02-04T20:46:22Z 置信度 0.70
• Tiny tweaks may mean a longer life
  crossref Carissa Wong 2026-01-24T00:18:47Z 置信度 0.70
• QuantumUQ: A Library for Uncertainty Quantification in Quantum Machine Learning
  Quantum machine learning (QML) models introduce unique sources of uncertainty arising from finite measurement shots, hardware noise, and variational optimization instability. Despite rapid progress in quantum algorithms, systematic uncertainty quantification (…
  crossref Ferhat Özgur Catak 2026-06-10T22:13:03Z 置信度 0.70
• <b>Banana Leaf Disease Prediction Using Machine Learning and Deep Learning Techniques</b>
  Banana cultivation plays a critical role in global agriculture; however, its productivity is severely affected by various foliar diseases such as Sigatoka, Panama wilt and Banana Bunchy Top Disease (BBTD). Early detection of these diseases is essential to mini…
  crossref Shivani Gupta 2026-05-15T09:24:18Z 置信度 0.70
• Ultralightweight sonar plus AI lets tiny drones navigate like bats
  crossref Nitin Sanket 2026-03-27T19:00:15Z 置信度 0.70
• [PDF] 10 scènes à sticker Tiny Cities. Avec 500 stickers par 404 Editions
  crossref Manuel Thurman 2026-04-25T21:00:58Z 置信度 0.70
• The Tiny Seed
  crossref Jules Pottle 2018-09-01T08:24:00Z 置信度 0.70
• Evaluating the Reliability of Explainable Machine Learning for Spacecraft Actuator Fault Detection
  crossref Pranav Narayan 2026-06-18T14:00:26Z 置信度 0.70
• Principles and Scope of Modern AI: Machine Learning, Deep Learning, Generative AI, and Agentic AI
  crossref Anurag Tiwari, Rakesh Kumar Yadav, Diwakar Yagyasen, Ankita Agarwal 等 2026-05-22T12:12:02Z 置信度 0.70
• Extreme learning machine based on Q-learning
  crossref Fengjun ZHU, Weidong ZOU, Bineng ZHONG 2026-05-20T07:37:38Z 置信度 0.70
• Teaching and Learning through AI in Machine Learning Courses: A Constructivist Approach Using Technology-Assisted Collaborative Learning
  crossref Smita Kulkarni, Dnyanda Hire 2026-04-28T19:46:14Z 置信度 0.70
• Multi-Year Flood Inundation Modelling in Kolhapur, India Using SAR Observations and Machine Learning
  crossref Shrikant Kate, Vidula Swami 2026-01-30T11:56:32Z 置信度 0.70
• Cross-Machine Generalization of Feature-Engineered Machine Learning for Relative Density Prediction in LPBF-Processed 18Ni300 Maraging Steel
  Laser Powder Bed Fusion (LPBF) enables the fabrication of high-performance metallic components, but achieving consistent relative density across different manufacturing systems remains challenging. Although machine learning (ML) has shown promise for predictin…
  crossref Aswin Karkadakattil, Arjun Kalath 2026-08-04T09:26:31Z 置信度 0.70
• Scrap weight prediction for different scrap types based on semantic segmentation and machine learning
  crossref Jihu Yin, Pengcheng Xiao, Bixia Zhang, Liguang Zhu 2026-06-26T05:03:25Z 置信度 0.70
• A tiny cone of reactivity
  Colliding molecules react only when their orientations and point of impact fall within a narrow range
  crossref Jonas Björk 2026-07-23T18:07:49Z 置信度 0.70
• An Advanced Stacking-based Machine Learning and Deep Learning Framework for Breast Cancer Prediction
  Breast cancer remains a critical global health challenge with early detection being vital for improving patient outcomes. Traditional diagnostic methods may be time-consuming and resource-intensive, highlighting the need for efficient machine learning solution…
  crossref Ibtasam Ur Rehman, Muhammad Islam, Basharat Hussain 2026-02-02T05:35:51Z 置信度 0.70
• ENSEMBLE LEARNING EM MACHINE LEARNING: FUNDAMENTOS, ESTRATÉGIAS E APLICAÇÕES
  Modelos individuais de Machine Learning frequentemente apresentam limitações relacionadas ao equilíbrio entre viés e variância, à sensibilidade às características dos dados e à capacidade de generalização. Nesse contexto, o Ensemble Learning reúne estratégias …
  crossref Eneida Glauce de Araújo Medeiros 2026-07-30T14:12:03Z 置信度 0.70
• Artificial intelligence and machine learning in healthcare
  crossref Risha Thakur, Anita Singh 2026-03-19T04:09:11Z 置信度 0.70
• Machine Learning and Deep Learning Algorithms in Surveillance Systems
  Abstract Machine learning (ML) and deep learning (DL) have been leveraged in surveillance systems to change the way of threat identification, criminal prevention, and public safety monitoring. In this chapter, we give an overview of related machine learning an…
  crossref Nitendra Kumar, Sandeep Mathur, Ramit Sehgal 2026-02-16T10:18:52Z 置信度 0.70
• Machine learning and deep learning for ground data deformation analytics: a comprehensive critical review
  Abstract Ground deformation threatens infrastructure integrity, environmental sustainability, and socio-economic resilience across rapidly urbanizing and tectonically active regions. Recent advances in Interferometric Synthetic Aperture Radar (InSAR), Global N…
  crossref Francis Quayson, Ishmael Yaw Dadson 2026-07-08T21:18:32Z 置信度 0.70
• Deep Learning and Machine Learning for Early Detection of Alzheimer’s Disease: A Systematic Review and Meta-Analysis
  Abstract Alzheimer’s disease is a progressive neurodegenerative disorder that poses a growing global public health challenge. Early and accurate diagnosis is critical for effective treatment, clinical trial participation, and disease management. This systemati…
  crossref Saketh Machiraju 2026-05-23T00:35:18Z 置信度 0.70
• How did so many theropod dinosaurs come to have tiny arms?
  crossref 2026-06-08T20:23:00Z 置信度 0.70
• Neuro-symbolic and Logic-Augmented Approaches for Scientific Machine Learning
  crossref Bikram Pratim Bhuyan, Amylia Ait Saadi, Yassine Meraihi, Amar Ramdane-Cherif 2026-07-23T12:57:12Z 置信度 0.70
• Scientists have discovered only a tiny fraction of living insect species
  crossref 2026-06-29T19:00:20Z 置信度 0.70
• Operator learning meets inverse problems
  crossref Nicholas H. Nelsen, Yunan Yang 2026-04-07T21:47:42Z 置信度 0.70
• Advancing Gastrointestinal Cancer Risk Prediction With Patient-Centered Machine Learning: Machine Learning Modeling Study
  Abstract Background Gastrointestinal (GI) cancers are a significant health concern in South Korea. Recently, machine learning (ML) models have emerged as powerful tools to support early screening efforts and identify people at risk before disease onset. Howeve…
  crossref Daina Baublyte, Jeonghee Lee, Madhawa Gunathilake, Jeongseon Kim 2026-02-17T15:25:07Z 置信度 0.70
• Effective Software Metrics Prediction For Bug Detection Using Machine Learning
  crossref Sushma Saini, Jai Bhagwan, Seema Rani, Sanjeev Kumar 2026-07-09T12:10:07Z 置信度 0.70
• Next-Generation Product Categorization in E-commerce using Quantum Machine Learning Approach over Virtualized Data Environment
  crossref Meenal N. Pande, Sanjay E. Yedey 2026-07-13T13:05:14Z 置信度 0.70
• Using Integrated Machine Learning Models On Educational Big Data To Predict Student Dropout Risk
  crossref Sahar Alamri, Faisal Alamri 2026-08-24T04:53:58Z 置信度 0.70
• Comparative Evaluation of Machine Learning and Deep Learning Models for Targeted Metaphor Detection
  Abstract Metaphor detection is an important natural language processing task because figurative language often conveys meanings that differ from literal word usage. This paper evaluates multiple machine learning and deep learning approaches for targeted metaph…
  crossref Muhammad Hassam Aslam Khan, Ninad Deshpande 2026-08-04T18:47:52Z 置信度 0.70
• An Intelligent Approach for Machine Downtime Prediction Using Ensembled Machine Learning Models
  In industrial settings, unplanned machine downtime is a serious risk to profitability, operational effectiveness, and production. In order to predict machine breakdowns before they occur, this research offers a machine learning-based predictive maintenance fra…
  crossref Suraj Arya, Deepak, Krishna Kumar Ujjawal 2026-04-09T14:40:33Z 置信度 0.70
• Generalized Physics-Informed Deep Learning Framework for Chemical Process Modeling
  The incorporation of mechanistic, first-principles chemical unit operation models into process modeling frameworks remains computationally challenging. Mechanistic models governed by complex nonlinear systems of ordinary and partial differential equations are …
  crossref Harshit Verma 2026-07-13T13:28:36Z 置信度 0.70
• Federated Machine Learning Outperforms Centralized Machine Learning for Fraud Detection: Evidence From 284,807 Real-World Transactions
  Aim/Purpose This study investigates whether federated machine learning (FML) can match or exceed centralized machine learning (CML) performance for financial fraud detection while maintaining complete data privacy. Background Financial fraud detection systems …
  crossref Samuel Sambasivam 2026-07-16T00:08:24Z 置信度 0.70
• AI and ML for Continuous Monitoring of Cognitive Learning
  crossref R. Kanthavel, R. Adline Freeda, R. Dhaya 2026-02-02T09:13:28Z 置信度 0.70
• Global Trends in Fake News Detection Research: A Bibliometric and Systematic Review of Machine Learning and Deep Learning Approaches (2015-2026)
  Fake news has become one of the most significant challenges in the digital information era due to the rapid growth of social media, online news platforms, and artificial intelligence-generated content. Researchers have proposed numerous machine learning and de…
  crossref Kazi Abdul Mannan, Hasin Sadad Abir 2026-08-06T08:58:46Z 置信度 0.70
• End Matter
  crossref 2026-03-10T08:53:34Z 置信度 0.70
• Understanding Specific Learning Disorders in youth: A machine learning approach to socio-emotional and cognitive aspects
  crossref Rachele Lievore, Alessandro Grecucci, Irene C. Mammarella 2026-04-17T16:34:02Z 置信度 0.70
• Machine Learning-augmented Rapid Screening and Scoring for an Effective Search for Lead Molecules in Computer-aided Drug Discovery
  The traditional process of lead molecule identification in drug discovery is often time-consuming, resource-intensive, and limited by the scale of molecular libraries that can be screened using conventional computational approaches. This chapter explores how m…
  crossref B. Jayaram, Dheeraj Kumar Chaurasia, Pradeep Pant 2026-07-22T08:41:26Z 置信度 0.70
• Hybrid Model For Multi-Feature SMS And URL Safety Classification Using Machine Learning
  crossref M.P Sudha, Dr.M Ramesh Kumar 2026-07-09T11:36:39Z 置信度 0.70
• Semantic-aware and variational mode decomposition-based multi-view learning for automotive categorization
  crossref Mengyao Liu 2026-08-14T14:55:38Z 置信度 0.70
• Deep learning models and speech data augmentation technologies for foreign language speech recognition
  crossref Li Liu 2026-08-14T14:55:31Z 置信度 0.70
• Data-Efficient and Fast Machine Learning Molecular Dynamics through Integrated Active Learning and Knowledge Distillation
  We develop data-efficient machine learning interatomic potentials (MLIPs) for fast molecular dynamics simulations combining DeePMD and MACE models within an active learning and knowledge distillation framework. Using liquid water as a case study, we first inde…
  crossref Xiliang Lian, Alfredo Pasquarello, Xiliang LIAN 2026-05-11T08:24:37Z 置信度 0.70
• Post-COVID Cardiovascular Risk Stratification Using Independent Machine Learning and Deep Learning Pipelines
  crossref M. Babu, Sandhiya C, Varsha P 2026-05-15T03:00:58Z 置信度 0.70
• Machine Learning for Security in Wireless Networks
  crossref Rohit M. Thanki, Komal R. Borisagar, Anjali Diwan 2025-08-12T04:57:41Z 置信度 0.70
• Virtual Learning Machine for Tiny Devices
  crossref Nozomi Kitagawa, Koichiro Yamauchi 2024-11-15T19:01:55Z 置信度 0.70
• Tiny genome pushes the boundaries of life
  crossref Jake Buehler 2026-02-28T00:16:17Z 置信度 0.70
• Machine Learning in Ecology
  crossref Jingli Ren, Yiwen Tao 2026-02-11T16:33:49Z 置信度 0.70
• Machine Learning in Precision Oncology: Integrating Multimodal Clinical Data for Treatment Selection
  This article is a preprint and has not yet been peer-reviewed. Not for clinical use. Integration of complex molecular, pathological, radiological, and longitudinal clinical data to guide treatment selection is becoming increasingly important for precision onco…
  crossref Simbarashe Magwenzi 2026-06-09T09:11:56Z 置信度 0.70
• Enhanced Energy Storage with Hybrid Nanoparticles and Machine Learning for Energy Sustainability
  crossref Arun Munusamy, Debabrata Barik, Sreejesh S.R. Chandran 2025-12-19T21:25:58Z 置信度 0.70
• Introduction to Wireless Communication and Machine Learning
  crossref Rohit M. Thanki, Komal R. Borisagar, Anjali Diwan 2025-08-12T04:57:39Z 置信度 0.70
• Causality-Powered Deep Learning Models for Stock Price Forecasting
  crossref Linxuan Ren, Qian Cheng, Ru Hou 2026-05-14T19:54:59Z 置信度 0.70
• Data-Driven Optimization of Multimedia Learning Interaction Using the Taguchi Method
  crossref Li-yu Tseng 2026-08-10T19:14:33Z 置信度 0.70
• CLewR: Curriculum Learning with Restarts for Machine Translation Preference Learning
  crossref Alexandra Dragomir, Florin Brad, Radu Tudor Ionescu 2026-07-01T12:25:50Z 置信度 0.70
• Explainable AI-Driven Machine Learning for Forecasting Marine Fisheries Production Using Environmental Predictors
  The marine capture fisheries sector of the Philippines employs approximately 2.3 million Filipinos, yet recent declines (including a 15.3% drop in Q1 2026 production relative to Q1 2025) underscore the need for forecasting systems resolved at the regional and …
  crossref Paul Bokingkito, Krisanadej Jaroensutasinee, Mullica Jaroensutasinee 2026-07-06T08:05:38Z 置信度 0.70
• Malicious QR Code Classification Using Machine Learning, Deep Learning, and Explainable AI
  crossref Melisa Alara Ozuberk, Ilkay Cinar 2026-03-10T19:50:51Z 置信度 0.70
• Artificial intelligence, machine learning and deep learning in advanced transportation systems, a review
  crossref Siavash Saki, Mohsen Soori 2025-05-21T11:33:09Z 置信度 0.70
• Machine Learning in Structure-based Drug Design
  In recent years, the identification and optimization of small molecules that bind and modulate protein function have become a critical step in early-stage drug discovery. Traditionally, structure-based drug design (SBDD) has relied on computational models to p…
  crossref Que-Huong Tran, Thi-Thuy-Nga Tran, Dac-Nhan Nguyen, Tan Thanh Mai 等 2026-07-22T08:41:26Z 置信度 0.70
• AUTOMATED GASTROINTESTINAL BLEED DETECTION USING WCEBLEEDGEN DEEP LEARNING MODEL
  Gastrointestinal bleeding is a serious medical WCE-BleedGen is a deep learning model that automatically detects and localizes bleeding in Wireless Capsule Endoscopy (WCE) images. It is trained on a large dataset of annotated WCE images, en­abling it to identif…
  crossref Manikandan Jayapal 2026-07-03T06:42:48Z 置信度 0.70
• TADPOLE: Tiny Autonomous Detection Platform for Off-board Lightweight Edge-computing
  crossref Caeden Taylor, Or D. Dantsker 2026-06-04T17:45:42Z 置信度 0.70
• Algorithmic Insights into Human Irrationality: Machine Learning Approaches to Detecting Cognitive Biases and Motivated Reasoning
  This study illuminates fundamental questions in behavioral science through advanced machine learning methodologies applied to large-scale public opinion data. Drawing on Kahneman and Tversky’s dual-process theory and Sunstein’s nudge architecture, we employ hi…
  crossref Sarthak Pattnaik, Chhayank Jain, Eugene Pinsky 2026-04-13T13:12:26Z 置信度 0.70
• Predictive Analytics In Sports For Transgender Lifestyle Enhancement: A Machine Learning Work
  crossref V. Preethi, P. Vanithamani, M. Indira 2026-07-30T15:18:57Z 置信度 0.70
• PaudhRog: Plant Leaf Disease Detection using Transfer Learning with InceptionResNetV2
  crossref Sheenam Middha, Abhay Kumar 2026-06-08T19:49:34Z 置信度 0.70
• Deep reinforcement learning for autonomous control of hole-doped Hubbard clusters: A comparative study
  Engineering electron correlations in quantum dot arrays demand navigation of high-dimensional, non-convex parameter spaces, where hole doping fundamentally alters the physics. We present a rigorous comparative study of two control paradigms for the 1-hole of h…
  crossref Shivanshu Dwivedi, Kalum Palandage 2026-03-23T13:39:36Z 置信度 0.70
• Data-consistent learning of inverse problems
  crossref Markus Haltmeier, Gyeongha Hwang 2026-04-07T21:47:36Z 置信度 0.70
• Machine Learning and Reinforcement Learning for Production Scheduling: A CiteSpace-Based Bibliometric Analysis
  crossref Hanchuan Li, Peng Pan 2026-05-19T19:47:30Z 置信度 0.70
• Towards Adaptive and Communication-Efficient Dynamic Federated Learning
  crossref Shunxin Guo, Jiaqi Lv, Qiufeng Wang, Xin Geng 2026-07-02T16:48:01Z 置信度 0.70
• Deep Reinforcement Learning-Based Approach for Abnormal Line Loss Diagnosis and Electricity Theft Detection in Distribution Transformer Areas
  crossref 2026-07-08T09:53:26Z 置信度 0.70
• Meta-learning-Based Integration of Set Encoder Outputs for MoonBoard Difficulty Estimation
  crossref Patrick Dharma, Takayasu Fushimi 2026-06-11T11:30:25Z 置信度 0.70
• Multi-Modal Driver Safety System Using Deep Learning and Machine Learning
  crossref Joshua Joseph, Sritama Roy 2026-03-31T19:48:45Z 置信度 0.70
• Machine learning and deep learning in river-basin modeling: A comprehensive review
  crossref Muhammad Waqas, Mohsin Nawaz 2026-05-02T14:52:02Z 置信度 0.70
• Introduction to multimodal data
  crossref 2026-08-25T07:28:12Z 置信度 0.70
• Uncovering Hidden Patterns: Customer Segmentation using Machine Learning
  crossref Harsheet Kaur 2026-05-28T06:30:08Z 置信度 0.70
• Quantifying and Mitigating Uncertainty: A Cross-Disciplinary Analysis in Machine Learning, Quantitative Finance, and Microeconomics
  The classification, quantification, and mitigation of uncertainty remain central challenges across data-driven disciplines. This paper formalizes the theoretical distinction between aleatoric (statistical noise) and epistemic (systemic ignorance) uncertainty. …
  crossref Pavan Mullapudi 2026-04-10T06:48:07Z 置信度 0.70
• Analysis And Classification Of Adversarial Machine Learning Attacks Against Machine Learning-Based Network Intrusion Detection Systems
  crossref Mr.Y.H.S.S. Phaneedra 2026-04-09T10:22:13Z 置信度 0.70
• A Comprehensive Review of Machine Learning and Deep Learning Approaches for Crop Yield Prediction
  Crop yield prediction is essential for improving agricultural productivity, resource management, and food security in the face of climate change and increasing population demands [1], [5]. Recent advances in Machine Learning (ML) and Deep Learning (DL) have si…
  crossref Pavan Sahu, Om Prakash Karada 2026-08-19T08:31:31Z 置信度 0.70
• Tiny boats demonstrate a new nanolithography technique
  crossref Sarah Wells 2026-02-06T14:49:38Z 置信度 0.70
• Temporal Uncertainty and Reliability of EMG-Based Machine Learning During Dynamic Contractions
  crossref Md Asjad Raza, Raghuram Karthik Desu, Sreejith Mohan 2026-07-15T20:02:01Z 置信度 0.70
• Sustainability Integration in Corporate Governance and Accounting Systems: Global Perspectives
  crossref 2026-06-15T05:23:10Z 置信度 0.70
• Applied Machine Learning: Real-World Models, Tools, and Solutions
  crossref 2026-03-10T05:19:16Z 置信度 0.70
• The Business Multiverse: Exploring Commerce and Management Across Parallel Realities
  crossref 2026-06-15T05:23:10Z 置信度 0.70
• Infant Cry Classification using Machine Learning and Deep Learning Techniques
  crossref Keerthi Sri Gomada, Christina Joshy, Betty Paulraj 2026-06-18T20:07:15Z 置信度 0.70
• Statistical and Machine Learning Analysis on the Effectiveness of Computer-Aided Learning (CAL)
  crossref Reena, Sangeeta 2026-04-23T19:57:13Z 置信度 0.70
• Chemical Understanding with Machine Learning and Quantum Computers
  crossref 2026-07-07T11:43:06Z 置信度 0.70
• FRONT MATTER
  crossref 2026-07-02T03:45:58Z 置信度 0.70
• Machine learning in data analysis and data augmentation for Raman spectroscopy
  crossref E.S.Prikhozhenko 2026-07-31T18:04:45Z 置信度 0.70
• Algorithmic Curatorial Shift
  Television program scheduling has long been an exercise in editorial authority: decisions regarding which programs to air, when, and in what order have shaped viewer behavior, structured the revenue logic of commercial broadcasting, and reproduced the broader …
  crossref Nimet Ersin 2026-08-27T18:38:07Z 置信度 0.70