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E-grāmata: Artificial Intelligence XLI: 44th SGAI International Conference on Artificial Intelligence, AI 2024, Cambridge, UK, December 17-19, 2024, Proceedings, Part I

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  • Formāts: EPUB+DRM
  • Sērija : Lecture Notes in Computer Science 15446
  • Izdošanas datums: 28-Nov-2024
  • Izdevniecība: Springer International Publishing AG
  • Valoda: eng
  • ISBN-13: 9783031779152
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  • Formāts: EPUB+DRM
  • Sērija : Lecture Notes in Computer Science 15446
  • Izdošanas datums: 28-Nov-2024
  • Izdevniecība: Springer International Publishing AG
  • Valoda: eng
  • ISBN-13: 9783031779152

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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 1719, 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.