{"product_id":"9783031779145","title":"Artificial Intelligence XLI : 44th SGAI International Conference on Artificial Intelligence, AI 2024, Cambridge, UK, December 17-19, 2024, Proceedings, Part I (Lecture Notes in Computer Science 15446) (2025. xvii, 361 S. XVII, 361 p. 125 illus., 27 illus.","description":"\u003cp\u003eThis 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.\u003c\/p\u003e\u003cp\u003eThe 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: - \u003c\/p\u003e\u003cp\u003ePart I: Neural nets; Deep learning; Large language models; Machine learning; Evolutionary and genetic algorithms; Knowledge management, Short Technical Papers.\u003c\/p\u003e\u003cp\u003ePart II: Machine vision; Evaluation of AI systems; Applications of machine learning; Other AI applications, Short Application Papers.\u003c\/p\u003e \u003cp\u003e\u003cstrong\u003e.- Technical Papers.\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e.- NER Explainability Framework: Utilizing LIME to Enhance Clarity and Robustness in Named Entity Recognition.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e.- Neural Nets. \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e.- Revealing limitations of ResNet models for deep evaluation in chess.\u003c\/p\u003e\u003cp\u003e.- Quasi Biologically Plausible Category Learning.\u003c\/p\u003e\u003cp\u003e.- On the Development of a Pixel-wise Plastic Waste Identification System for Multispectral Remote Sensing Applications.\u003c\/p\u003e\u003cp\u003e.- Streamlining Attention for Text Classification: Sequence Length Reduction with Pooling Attention.\u003c\/p\u003e\u003cp\u003e.- LSTM for Modelling and Predictive Control of Multivariable Processes.\u003c\/p\u003e\u003cp\u003e.- Structured Radial Basis Function Network: Modelling Diversity for Multiple Hypotheses Prediction.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e.- Deep Learning. \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e.- Bitcoin Forecasting using Deep Learning and Time Series Ensemble Techniques.\u003c\/p\u003e\u003cp\u003e.- TRAPL: Transformer-based Patch Learning For Enhancing Semantic Representations Using Aggregated Features to Estimate Patch-Class Distribution.\u003c\/p\u003e\u003cp\u003e.- DATE: Derivative Alignment Training for Extrapolation with Neural Networks.\u003c\/p\u003e\u003cp\u003e.- Interactive Simulator Framework for XAI Applications in Aquatic Environments.\u003c\/p\u003e\u003cp\u003e.- Detection of vascular leukoencephalopathy in CT images.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e.- Large Language Models. \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e.- PlanBERT: From Messy Zonal Plans to Informative Vector Embeddings.\u003c\/p\u003e\u003cp\u003e.- ArgueMapper Assistant: Interactive Argument Mining Using Generative Language Models.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e.- Machine Learning. \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e.- Contextual Transformers for Goal-Oriented Reinforcement Learning.\u003c\/p\u003e\u003cp\u003e.- Localized Affinity-based Reinforcement Learning for Interpretable State-specific Decision-making.\u003c\/p\u003e\u003cp\u003e.- Navigating the Landscape of Case Fidelity and Competence in Case-Based Reasoning.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e.- Evolutionary and Genetic Algorithms. \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e.- Tree-based Genetic Programming for Evolutionary Analog Circuit with Approximate Shapley Value.\u003c\/p\u003e\u003cp\u003e.- A Dominance-based Surrogate Classifier for Multi-Objective Evolutionary Algorithms.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e.- Knowledge Management. \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e.- A Homogeneous Approach to Reasoning Over Global Geographic Data.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e.- Short Technical Papers.\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e.- OK Google, what is the stock forecast for next week? Leveraging Search Engines for Data Collection, Sentiment Analysis and Stock Predictions.\u003c\/p\u003e\u003cp\u003e.- University News: A New Data Source for NLP Bias Research.\u003c\/p\u003e\u003cp\u003e.- Enhancing Nepali Text Understanding with Machine Translation and LoRA Fine-Tuning of Open-Source LLM.\u003c\/p\u003e\u003cp\u003e.- Audio-visual emotion recognition using Deep Learning methods.\u003c\/p\u003e\u003cp\u003e.- Spatial interpolation of air quality: A UK Case study.\u003c\/p\u003e\u003cp\u003e.- Talk like a local: Evaluating Large Language Models for Arabic Dialect Translation Using Similarity Scores.\u003c\/p\u003e\u003cp\u003e.- On Monadic Binary, with Application to Machine Understanding.\u003c\/p\u003e\u003cp\u003e.- A Proposed ELM Ensemble Approach for Predicting Railway Delays.\u003c\/p\u003e\u003cp\u003e.- Semantic Bone Structure Segmentation in 2D Image Data: Towards Total Knee Arthroplasty.\u003c\/p\u003e","brand":"SPRINGER, BERLIN; SPRINGER NATURE SWITZERLAND; SPRING","offers":[{"title":"Default Title","offer_id":48865546010859,"sku":"00000_00000_00000_00000","price":155.63,"currency_code":"SGD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0758\/4484\/5803\/files\/9783031779145-1.jpg?v=1781717792","url":"https:\/\/kinokuniya.com.sg\/zh\/products\/9783031779145","provider":"Books Kinokuniya Singapore","version":"1.0","type":"link"}