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[null,"1.","Record Nr.",null,"UNINA9910983367203321"]
[null,null,"Autore",null,"Bramer Max"]
[null,null,"Titolo",null,"Artificial Intelligence XLI : 44th SGAI International Conference on Artificial Intelligence, AI 2024, Cambridge, UK, December 17–19, 2024, Proceedings, Part II / / edited by Max Bramer, Frederic Stahl"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025"]
[null,null,"ISBN",null,"9783031779183"]
[{"$nulls":4},"3031779185"]
[null,null,"Edizione",null,"[1st ed. 2025.]"]
[null,null,"Descrizione fisica",null,"1 online resource (285 pages)"]
[null,null,"Collana",null,"Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 15447"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Computer engineering"]
[{"$nulls":4},"Computer networks"]
[{"$nulls":4},"Computers"]
[{"$nulls":4},"Application software"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Computer Engineering and Networks"]
[{"$nulls":4},"Computing Milieux"]
[{"$nulls":4},"Computer and Information Systems Applications"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"-- Application Papers.  -- Adaptive CNN Method For Prostate MR Image Segmentation Using Ensemble Learning.  -- Machine Vision.  -- Optimizing Autonomous Vehicle Racing using Reinforcement Learning with Pre-trained Embeddings for Dimensionality Reduction.  -- Semantic Segmentation for Landslide Detection using Segformer.  -- Vision-Based Human Fall Detection using 3D Neural Networks.  -- Drone-Assisted Infrared Thermography and Machine Learning for Enhanced Photovoltaic Defect Detection: A Comparative Study of ViTs and YOLOv8.  -- Evaluation of AI Systems.  -- Evaluating Algorithms for Missing Value Imputation in Real Battery Data.  -- Using Pseudo Cases and Stratified Case-Based Reasoning to Generate and Evaluate Training Adjustments for Marathon Runners.  -- Applications of Machine Learning.  -- Emotion Detection in Hindi language using GPT and BERT.  -- Classification and Recommendation of Mental Health Assistance Events Using an RNN-LSTM, Fast-and-Frugal Trees and "]
[{"$nulls":4},"Weighted Sum System.  -- Digit Detection: Localizing and Convoluting.  -- Djinn - Data Journalism Interface for Newsgathering and Notifications.  -- Advancing Financial Text Sentiment Analysis with Deep Learning and Ensemble Models.  -- Other AI Applications.  -- Explaining a Staff Rostering Problem using Partial Solutions.  -- Formalise Regulations for Autonomous Vehicles with Right-Open Temporal Deontic Defeasible Logic.  -- SLANGO - The Initial Blueprint of Privacy-Oriented Legal Query Assistance: Exploring the potential of Retrieval Augmented Generation for German Law using SPR.  -- Short Application Papers.  -- An Ensemble Modelling of Feature Engineering and Predictions for Enhanced Fake News Detection.  -- A Child-Robot Interaction Experiment to Analyze Gender Stereotypes in the Perception of Mathematical Abilities.  -- Reinforcement Learning for Patient Scheduling with Combinatorial Optimisation.  -- Nursing Activity Recognition for Automated Care Documentation in Clinical Settings.  -- Exploring Efficient Job Shop Scheduling Using Deep Reinforcement Learning.  -- Respiratory Disease Detection Using Deep Convolutional Transformer Models.  -- Evaluating the performance of LLMs when translating Saudi Arabic as Low Resource Language.  -- Bi-directional LSTM Applied to the Maritime Target Motion Analysis Problem."]
[null,null,null,"Sommario/riassunto","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."]