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AI 2024: advances in artificial intelligence : 37th Australasian Joint Conference on Artificial Intelligence, AI 2024, Melbourne, VIC, Australia, November 25-29, 2024 ; proceedings, part II / Mingming Gong, Yiliao Song, Yun Sing Koh, Wei Xiang, Derui Wang, editors

By: Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Lecture notes in computer science ; Lecture notes in artificial intelligence ; 15443Publisher: Singapore : Springer, [2025]Description: 1 Online-RessourceISBN:
  • 9789819603510
Subject(s): Genre/Form: Additional physical formats: 9789819603503 | 9789819603527 | Erscheint auch als: AI 2024: advances in artificial intelligence ; Part 2. Druck-Ausgabe Singapore : Springer, 2025. xix, 460 SeitenDDC classification:
  • 006.3 23
DOI: DOI: 10.1007/978-981-96-0351-0Online resources: Summary: -- Reinforcement Learning and Robotics. -- ECoDe: A Sample-Efficient Method for Co-Design of Robotic Agents. -- Causally driven hierarchies for Feudal Multi-Agent Reinforcement Learning. -- Graceful Task Adaptation with a Bi-Hemispheric RL Agent. -- Towards Virtual Character Control via Partial Story Sifting. -- Boosting Reinforcement Learning Algorithms in Continuous Robotic Reaching Tasks using Adaptive Potential Functions. -- Online Deep Reinforcement Learning of Servo Control for a Small-Scale Bio-Inspired Wing. -- Posterior Tracking Algorithm for Multi-objective Classification Bandits. -- Learning Algorithms -- Approximate Nearest Neighbour Search on Dynamic Datasets: An Investigation. -- Pathwise Gradient Variance Reduction with Control Variates in Variational Inference. -- Active Continual Learning: On Balancing Knowledge Retention and Learnability. -- Bayesian Parametric Proportional Hazards Regression with the Fused Lasso. -- Revisiting Bagging for Stochastic Algorithms. -- Sampling of Large Probabilistic Graphical Models Using Arithmetic Circuits. -- Importance-based Pruning for Genetic Programming based Symbolic Regression. -- Quantifying Manifolds: Do the Manifolds Learned by Generative Adversarial Networks Converge to the Real Data Manifold?. -- Equality Generating Dependencies in Description Logics via Path Agreements. -- Computer Vision -- End-to-end Truck Speed Detection using Deep Multi-Task Learning. -- Real-Time Lightweight 3D Hand-Object Pose Estimation Using Temporal Graph Convolution Networks. -- New Perspectives for the Deep Learning Based Photography Aesthetics Assessment. -- 3DSSG-Cap: A Caption Enhanced Dataset for 3D Visual Grounding. -- Multi-scale Cooperative Multimodal Transformers for Multimodal Sentiment Analysis in Videos. -- Chain of Thought Prompting in Vision-Language Model for Vision Reasoning Tasks. -- Enabling Visual Intelligence by Leveraging Visual Object States in a Neurosymbolic Framework. -- AI for Healthcare -- A Self-Adaptive Framework for Efficient Cell Detection and Segmentation in Histopathological Images with Minimal Expert Input. -- Learning Low-Energy Consumption Obstacle Detection Models for the Blind. -- Claimsformer: Pretrained Transformer for Administrative Claims Data to Predict Chronic Conditions. -- Online Machine Learning for Real-Time Cell Culture Process Monitoring. -- Motif-induced Subgraph Generative Learning for Explainable Neurological Disorder Detection. -- Multimodal Hyperbolic Graph Learning for Alzheimer’s Disease Detection. -- Real-Time Human Activity Recognition Using Non-Intrusive Sensing and Continual Learning. -- Unsupervised dMRI Artifact Detection via Angular Resolution Enhancement and Cycle Consistency Learning. -- Assessment of Left Atrium Motion Deformation Through Full Cardiac Cycle. -- Vision-Based Abnormal Action Dataset for Recognising Body Motion Disorders.Summary: This two-volume set LNAI 15442-15443 constitutes the refereed proceedings of the 37th Australasian Joint Conference on Artificial Intelligence, AI 2024, held in Melbourne, VIC, Australia, during November 25-29, 2024. The 59 full papers presented together with 3 short papers were carefully reviewed and selected from 108 submissions. Part 1: Knowledge Representation and NLP; Trustworthy and Explainable AI; Machine Learning and Data Mining. Part 2: Reinforcement Learning and Robotics; Learning Algorithms; Computer Vision; AI for Healthcare.PPN: PPN: 1909519766Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SCS | ZDB-2-SXCS | ZDB-2-LNC
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