Artificial Intelligence XLI

44th SGAI International Conference on Artificial Intelligence, AI 2024, Cambridge, UK, December 17¿19, 2024, Proceedings, Part I
Herausgegeben:Bramer, Max; Stahl, Frederic

• Broschiertes Buch

Produktbeschreibung

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.

Produktdetails

• Lecture Notes in Computer Science 15446
• Verlag: Springer / Springer Nature Switzerland / Springer, Berlin
• Artikelnr. des Verlages: 978-3-031-77914-5
• Seitenzahl: 380
• Erscheinungstermin: 29. November 2024
• Englisch
• Abmessung: 235mm x 155mm x 21mm
• Gewicht: 575g
• ISBN-13: 9783031779145
• ISBN-10: 3031779142
• Artikelnr.: 71902159

Inhaltsangabe

.- 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.