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A Lightweight AI-Based Approach for Drone Jamming Detection
Published 2025-01-01Get full text
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502
Rice seed integrity evaluation: Developing a rapid onsite system to check seed fraud using a portable NIR spectroscopic device coupled with smartphone technology
Published 2025-09-01“…Among the classification algorithms used, Random Forest (RF) achieved 100 % accuracy for rice seed identification and 97.38 % for paddy identification in the test sets. …”
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Development of an AI-Based Self-Diagnosis System for Tropical Diseases
Published 2025-05-01Get full text
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AI-enhanced fire detection and suppression system for autonomous ships
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Enhancing mechanical and bioinspired materials through generative AI approaches
Published 2025-01-01“…As generative AI continues to evolve, its integration promises to revolutionize engineering design and drive the field towards unprecedented levels of efficiency, thus turns information into knowledge.…”
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AI-Powered Innovations in Food Safety from Farm to Fork
Published 2025-06-01“…This article systematically reviews the core applications of AI in the orbit of food safety. First, in the production and quality control of primary food sources, the integration of spectral data with AI efficiently identifies pest and disease, food spoilage, and pesticide and veterinary drug residues. …”
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510
Ground-truth is law: The invisible conceptual work behind AI
Published 2025-06-01“…These datasets, shaped by a range of actors across the AI production chain, subtly guide algorithmic operations under the guise of neutrality. …”
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511
Hybrid Models for Forecasting Allocative Localization Error in Wireless Sensor Networks
Published 2025-12-01“…The approach utilizes Radial Basis Function (RBF) models enhanced with advanced optimization algorithms, including Coot Optimization Algorithm (COA), Smell Agent Optimization (SAO), and Northern Goshawk Optimization (NGO) to improve ALE prediction accuracy. …”
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AI-assisted ophthalmic imaging for early detection of neurodegenerative diseases
Published 2025-05-01“…However, challenges such as model interpretability, dataset biases, and ethical considerations must be addressed to ensure the responsible integration of AI into clinical practice. Future research should focus on refining AI algorithms, integrating multimodal imaging techniques, and developing predictive biomarkers to optimize early intervention strategies for neurodegenerative diseases. …”
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From Code to Life: The AI‐Driven Revolution in Genome Editing
Published 2025-08-01“…Additionally, AI‐powered tools facilitate large‐scale data integration, accelerating functional genomics and therapeutic genome editing. …”
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Leveraging AI for Enhanced Operational Risk Management in Sports Events
Published 2024-01-01“…This article explores the integration of artificial intelligence (AI) into operational risk management at sporting events. …”
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AI in dermatology: a comprehensive review into skin cancer detection
Published 2024-12-01“…Integrating AI tools into clinical workflows is critical to maximizing their utility and effectiveness. …”
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AI-Driven Robotics: Innovations in Design, Perception, and Decision-Making
Published 2025-07-01“…Artificial intelligence (AI), driven by large datasets and advanced algorithms, plays a pivotal role in addressing these challenges and advancing robotics. …”
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The dual-edged potential of AI autonomously defining loss functions
Published 2025-07-01Get full text
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AI in biomedical research: unleashing the potential of a transformative partnership
Published 2024-02-01“…The integration of AI into Biomedical Sciences is yet not free from its set of challenges. …”
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Opportunities and challenges of AI-systems in political decision-making contexts
Published 2025-03-01“…However, using such technologies for certainty purposes in political decision-making contexts also presents several challenges—and if these challenges are not addressed, the integration of AI in political decision-making could lead to adverse consequences. …”
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Privacy, ethics, transparency, and accountability in AI systems for wearable devices
Published 2025-06-01“…The integration of artificial intelligence (AI) and machine learning (ML) into wearable sensor technologies has substantially advanced health data science, enabling continuous monitoring, personalised interventions, and predictive analytics. …”
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