Arai / Lorenz Intelligent Systems and Applications

Proceedings of the 2026 Intelligent Systems Conference (IntelliSys), Volume 2
Erscheinungsjahr 2026
ISBN: 978-3-032-32726-0
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 853 Seiten

Reihe: Springer Nature Proceedings excluding Computer Science

This book presents the proceedings of the 12th Intelligent Systems Conference 2026 (IntelliSys 2026), held on September 3–4, 2026, in Amsterdam, The Netherlands, and contains selected peer-reviewed papers presenting recent advances, innovative methodologies, and practical applications in the field of intelligent systems and related technologies.
The conference served as an international platform for researchers, academicians, scientists, and industry professionals to exchange ideas, share research findings, and discuss current challenges and future directions in intelligent computing. The accepted contributions cover a wide range of topics, including Artificial Intelligence, Machine Learning, Computer Vision, Internet of Things (IoT), Cyber-Physical Systems, Data Science, and Intelligent Computing. All submissions underwent a rigorous double-blind peer-review process conducted by the Technical Program Committee to ensure high standards of quality, originality, technical merit, and relevance to the conference themes.
These proceedings reflect the multidisciplinary nature and continuing growth of intelligent systems research.

Zielgruppe

Research

Autoren/Hrsg.

Arai, Kohei

Lorenz, Pascal

Inhaltsverzeichnis

A Lightweight Machine Learning Approach for Smartphone-Based Pig Weight Estimation.- Vanishing Depth: Training Generalized Depth Adapters with Sinusoidal Depth Preprocessing for Pretrained RGB Encoders.- Detection of Foraging and Sanitation Behaviors in Stingless Bee Hives Using Deep Learning.- Design of a Query Expression for Multi-Dimensional Graph Warehousing.- PCA-Based Interpretable Knowledge Representation and Analysis of Geometric Design Parameters.- Latent Boost: Enhancing Interpretability Through Loss-Defined Classification Objective in Structured Latent Spaces.- Towards Better Dining Sector: Interpretable Sentiment Analysis of Jordanian Restaurants’ Reviews.- A Multi-Objective Framework for Selecting Plausible and Causally Consistent Counterfactual Explanations Guided by SHAP.- From Risk Score to Audit Explanation: Two-Stage Procurement Fraud Detection in ERP.- Blockchain-Enabled Federated Learning for Collaborative Autonomous Vehicles.