Artificial Intelligence XLI

44th SGAI International Conference on Artificial Intelligence, AI 2024, Cambridge, UK, December 17–19, 2024, Proceedings, Part I

AvMax Bramer,Frederic Stahl

Häftad, Engelska, 2024

Del 15446 i serien Lecture Notes in Computer Science

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2024-11-29
Mått:155 x 235 x 21 mm
Vikt:575 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:361
Förlag:Springer International Publishing AG
ISBN:9783031779145

Utforska kategorier

Informationsteknik: allmänt inom Data och IT
Artificiell intelligens inom Data och IT
Hårdvara inom Data och IT

Innehållsförteckning

.- 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.