Artificial Intelligence XLI
Springer International Publishing (Verlag)
978-3-031-77914-5 (ISBN)
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This two-volume set, LNAI 15446 and LNAI 15447, constitutes the refereed proceedings of the 44th SGAI International Conference on Artificial Intelligence, AI 2024, held in Cambridge, UK, during December 17-19, 2024.
The 36 full papers and 18 short papers presented in these two volumes were carefully reviewed and selected from 80 submissions. Part I includes papers from the Technical stream, whereas Part II includes papers from the Application stream. These volumes are organized into the following topical sections: -
Part I: Neural nets; Deep learning; Large language models; Machine learning; Evolutionary and genetic algorithms; Knowledge management, Short Technical Papers.
Part II: Machine vision; Evaluation of AI systems; Applications of machine learning; Other AI applications, Short Application Papers.
.- Technical Papers.
.- NER Explainability Framework: Utilizing LIME to Enhance Clarity and Robustness in Named Entity Recognition.
.- Neural Nets.
.- Revealing limitations of ResNet models for deep evaluation in chess.
.- Quasi Biologically Plausible Category Learning.
.- On the Development of a Pixel-wise Plastic Waste Identification System for Multispectral Remote Sensing Applications.
.- Streamlining Attention for Text Classification: Sequence Length Reduction with Pooling Attention.
.- LSTM for Modelling and Predictive Control of Multivariable Processes.
.- Structured Radial Basis Function Network: Modelling Diversity for Multiple Hypotheses Prediction.
.- Deep Learning.
.- Bitcoin Forecasting using Deep Learning and Time Series Ensemble Techniques.
.- TRAPL: Transformer-based Patch Learning For Enhancing Semantic Representations Using Aggregated Features to Estimate Patch-Class Distribution.
.- DATE: Derivative Alignment Training for Extrapolation with Neural Networks.
.- Interactive Simulator Framework for XAI Applications in Aquatic Environments.
.- Detection of vascular leukoencephalopathy in CT images.
.- Large Language Models.
.- PlanBERT: From Messy Zonal Plans to Informative Vector Embeddings.
.- ArgueMapper Assistant: Interactive Argument Mining Using Generative Language Models.
.- Machine Learning.
.- Contextual Transformers for Goal-Oriented Reinforcement Learning.
.- Localized Affinity-based Reinforcement Learning for Interpretable State-specific Decision-making.
.- Navigating the Landscape of Case Fidelity and Competence in Case-Based Reasoning.
.- Evolutionary and Genetic Algorithms.
.- Tree-based Genetic Programming for Evolutionary Analog Circuit with Approximate Shapley Value.
.- A Dominance-based Surrogate Classifier for Multi-Objective Evolutionary Algorithms.
.- Knowledge Management.
.- A Homogeneous Approach to Reasoning Over Global Geographic Data.
.- Short Technical Papers.
.- OK Google, what is the stock forecast for next week? Leveraging Search Engines for Data Collection, Sentiment Analysis and Stock Predictions.
.- University News: A New Data Source for NLP Bias Research.
.- Enhancing Nepali Text Understanding with Machine Translation and LoRA Fine-Tuning of Open-Source LLM.
.- Audio-visual emotion recognition using Deep Learning methods.
.- Spatial interpolation of air quality: A UK Case study.
.- Talk like a local: Evaluating Large Language Models for Arabic Dialect Translation Using Similarity Scores.
.- On Monadic Binary, with Application to Machine Understanding.
.- A Proposed ELM Ensemble Approach for Predicting Railway Delays.
.- Semantic Bone Structure Segmentation in 2D Image Data: Towards Total Knee Arthroplasty.
Erscheint lt. Verlag | 10.1.2025 |
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Reihe/Serie | Lecture Notes in Artificial Intelligence | Lecture Notes in Computer Science |
Zusatzinfo | XIV, 342 p. 107 illus. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
Schlagworte | Artificial Intelligence • Case-Based Reasoning • Constraint Satisfaction • Deep learning • Fuzzy Logic • Intelligent Systems • Large Language Models • machine learning • Natural Language Processing • Neural networks • Rule Induction • vision systems |
ISBN-10 | 3-031-77914-2 / 3031779142 |
ISBN-13 | 978-3-031-77914-5 / 9783031779145 |
Zustand | Neuware |
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