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020		▼a9789819603510▼9978-981-96-0351-0
024		▼a10.1007/978-981-96-0351-0▼2doi
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245	00	▼aAI 2024: Advances in Artificial Intelligence▼h[electronic resource] :▼b37th Australasian Joint Conference on Artificial Intelligence, AI 2024, Melbourne, VIC, Australia, November 25–29, 2024, Proceedings, Part II /▼cedited by Mingming Gong, Yiliao Song, Yun Sing Koh, Wei Xiang, Derui Wang.
250		▼a1st ed. 2025.
264		▼aSingapore :▼bSpringer Nature Singapore :▼bImprint: Springer,▼c2025.
300		▼aXIX, 460 p. 140 illus., 130 illus. in color.▼bonline resource.
336		▼atext▼btxt▼2rdacontent
337		▼acomputer▼bc▼2rdamedia
338		▼aonline resource▼bcr▼2rdacarrier
347		▼atext file▼bPDF▼2rda
490		▼aLecture Notes in Artificial Intelligence,▼x2945-9141 ;▼v15443
505		▼a -- 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.
520		▼aThis 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.
650		▼aArtificial intelligence.
650		▼aComputer networks .
650		▼aData mining.
650		▼aApplication software.
650		▼aComputer vision.
650		▼aArtificial Intelligence.
650		▼aComputer Communication Networks.
650		▼aData Mining and Knowledge Discovery.
650		▼aComputer and Information Systems Applications.
650		▼aComputer Vision.
700		▼aGong, Mingming.▼eeditor.▼0(orcid)0000-0001-7147-5589▼1https://orcid.org/0000-0001-7147-5589▼4edt▼4http://id.loc.gov/vocabulary/relators/edt
700		▼aSong, Yiliao.▼eeditor.▼0(orcid)0000-0002-6633-2695▼1https://orcid.org/0000-0002-6633-2695▼4edt▼4http://id.loc.gov/vocabulary/relators/edt
700		▼aKoh, Yun Sing.▼eeditor.▼0(orcid)0000-0001-7256-4049▼1https://orcid.org/0000-0001-7256-4049▼4edt▼4http://id.loc.gov/vocabulary/relators/edt
700		▼aXiang, Wei.▼eeditor.▼0(orcid)0000-0002-0608-065X▼1https://orcid.org/0000-0002-0608-065X▼4edt▼4http://id.loc.gov/vocabulary/relators/edt
700		▼aWang, Derui.▼eeditor.▼0(orcid)0000-0003-1388-7715▼1https://orcid.org/0000-0003-1388-7715▼4edt▼4http://id.loc.gov/vocabulary/relators/edt
710		▼aSpringerLink (Online service)
773		▼tSpringer Nature eBook
776		▼iPrinted edition:▼z9789819603503
776		▼iPrinted edition:▼z9789819603527
830		▼aLecture Notes in Artificial Intelligence,▼x2945-9141 ;▼v15443
856		▼uhttps://doi.org/10.1007/978-981-96-0351-0
912		▼aZDB-2-SCS
912		▼aZDB-2-SXCS
912		▼aZDB-2-LNC
950		▼aComputer Science (SpringerNature-11645)
950		▼aComputer Science (R0) (SpringerNature-43710)

AI 2024: Advances in Artificial Intelligence[electronic resource] :37th Australasian Joint Conference on Artificial Intelligence, AI 2024, Melbourne, VIC, Australia, November 25–29, 2024, Proceedings, Part II /edited by Mingming Gong, Yiliao Song, Yun Sing Koh, Wei Xiang, Derui Wang

종류

전자책

서명

저자명

Gong Mingming. editor Song Yiliao. editor Koh Yun Sing. editor Xiang Wei. editor Wang Derui. editor

판 사항

1st ed. 2025.

형태사항

XIX, 460 p 140 illus, 130 illus in color online resource.

주기사항

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.

내용주기

/ 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.

ISBN

9789819603510

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