國立高雄大學圖資館 |

Brain informatics16th International Conference, BI 2023, Hoboken, NJ, USA, August 1-3, 2023 : proceedings /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Brain informaticsedited by Feng Liu ... [et al.].
其他題名:	16th International Conference, BI 2023, Hoboken, NJ, USA, August 1-3, 2023 : proceedings /
其他題名:	BI 2023
其他作者:	Liu, Feng.
團體作者:
出版者:	Cham :Springer Nature Switzerland :2023.
面頁冊數:	xiii, 479 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Neural networks (Computer science)
電子資源:	https://doi.org/10.1007/978-3-031-43075-6
ISBN:	9783031430756$q(electronic bk.)

Brain informatics16th International Conference, BI 2023, Hoboken, NJ, USA, August 1-3, 2023 : proceedings /
Brain informatics16th International Conference, BI 2023, Hoboken, NJ, USA, August 1-3, 2023 : proceedings /[electronic resource] :BI 2023edited by Feng Liu ... [et al.]. - Cham :Springer Nature Switzerland :2023. - xiii, 479 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,139740302-9743 ;. - Lecture notes in computer science ;4891..

Cognitive and Computational Foundations of Brain Science: Fusing Structural and Functional Connectivity using Disentangled VAE for Detecting MCI -- Modulation of Beta Power as a Function of Attachment Style and Feedback Valence -- Harnessing the Potential of EEG in Neuromarketing with Deep Learning and Riemannian Geometry -- A Model of the Contribution of Interneuron Diversity to Recurrent Network Oscillation Generation and Information Coding -- Measuring Stimulus-Related Redundant and Synergistic Functional Connectivity with Single Cell Resolution in Auditory Cortex -- Fusing Simultaneously Acquired EEG and fMRI via Hierarchical Deep Transcoding -- Investigations of Human Information Processing Systems: Decoding Emotion Dimensions Arousal and Valence Elicited on EEG Responses to Videos and Images: A Comparative Evaluation -- Stabilize Sequential Data Representation via Attractor Module -- Investigating the Generative Dynamics of Energy-Based Neural Networks -- Exploring Deep Transfer Learning Ensemble for Improved Diagnosis and Classification of Alzheimer's Disease -- Brain Big Data Analytics, Curation and Management: Effects of EEG Electrode Numbers on Deep Learning-Based Source Imaging -- Graph Diffusion Reconstruction Model for Addictive Brain-Network Computing -- MR Image Super-Resolution using Wavelet Diffusion for Predicting Alzheimer's Disease -- Classification of Event-Related Potential Signals with a Variant of UNet Algorithm using a Large P300 Dataset -- Dyslexia Data Consortium Repository: A Data Sharing and Delivery Platform for Research -- Conversion from Mild Cognitive Impairment to Alzheimer's Disease: A Comparison of Tree-based Machine Learning Algorithms for Survival Analysis -- Predicting Individual Differences from Brain Responses to Music: A Comparison of Functional Connectivity Measure -- Multiplex Temporal Networks for Rapid Mental Workload Classification -- Super-Resolution MRH Reconstruction for Mouse Models -- Bayesian Time Series Classifier for Decoding Simple Visual Stimuli from Intracranial Activity -- Variability of Non-parametric HRF in Interconnectedness and its Association in Deriving Resting State Network -- BrainSegNeT: A Lightweight Brain Tumor Segmentation Model based on U-Net and Progressive Neuron Expansion -- Improving Prediction Quality of Face Image Preference using Combinatorial Fusion Algorithm -- MMDF-ESI: Multi-Modal Deep Fusion of EEG and MEG for Brain Source Imaging -- Rejuvenating Classical Source Localization Methods with Spatial Graph Filters -- Prediction of Cannabis Addictive Patients with Graph Neural Networks -- Unsupervised Sparse-view Backprojection via Convolutional and Spatial Transformer Networks -- Latent Neural Source Recovery via Transcoding of Simultaneous EEG-fMRI -- Informatics Paradigms for Brain and Mental Health Research: Increasing the Power of Two-Sample T-Tests in Health Psychology using a Compositional Data Approach -- Estimating Dynamic Posttraumatic Stress Symptom Trajectories with Functional Data Analysis -- Comparison Between Explainable AI Algorithms for Alzheimer's Disease Prediction Using EfficientNet Models -- Social and Non-social Reward Learning Contexts for Detection of Major Depressive Disorder using EEG: A Machine Learning Approach -- Transfer Learning-Assisted DementiaNet: A Four Layer Deep CNN for Accurate Alzheimer's Disease Detection from MRI Images -- Multimodal Approaches for Alzheimer's Detection Using Patients' Speech and Transcript -- Brain-Machine Intelligence and Brain-Inspired Computing -- Exploiting Approximate Joint Diagonalization for Covariance Estimation in Imagined Speech Decoding -- Automatic Sleep-Wake Scoring with Optimally Selected EEG Channels from High-Density EEG -- EEG Source Imaging of Hand Movement-Related Areas: An Evaluation of the Reconstruction Accuracy with Optimized Channels -- Bagging the Best: A Hybrid SVM-KNN Ensemble for Accurate and Early Detection of Alzheimer's and Parkinson's Diseases -- Roe: A Computational-Efficient Anti-Hallucination Fine-Tuning Technology for Large Language Model Inspired by Human Learning Process -- The 5th International Workshop on Cognitive Neuroscience of Thinking and Reasoning: Brain Intervention Therapy Dilemma: Functional Recovery versus Identity.

This book constitutes the proceedings of the 16th International Conference on Brain Informatics, BI 2023, which was held in Hoboken, NJ, USA, during August 1-3, 2023. The 40 full papers presented in this book were carefully reviewed and selected from 101 submissions. The papers are divided into the following topical sections: cognitive and computational foundations of brain science; investigations of human Information processing systems; brain big data analytics, curation and management; informatics paradigms for brain and mental health research; brain-machine intelligence and brain-inspired computing; and the 5th international workshop on cognitive neuroscience of thinking and reasoning.

ISBN: 9783031430756$q(electronic bk.)

Standard No.: 10.1007/978-3-031-43075-6doiSubjects--Topical Terms:

181982
Neural networks (Computer science)

LC Class. No.: QA76.87

Dewey Class. No.: 006.32

Brain informatics16th International Conference, BI 2023, Hoboken, NJ, USA, August 1-3, 2023 : proceedings /
LDR:06171nmm a2200361 a 4500 001 651157
003 DE-He213
005 20230912081328.0
006 m d
007 cr nn 008maaau
008 240327s2023 sz s 0 eng d
020 $a 9783031430756$q(electronic bk.)
020 $a 9783031430749$q(paper)
024 7 $a 10.1007/978-3-031-43075-6 $2 doi
035 $a 978-3-031-43075-6
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.87
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.32 $2 23
090 $a QA76.87 $b .I61 2023
111 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
245 1 0 $a Brain informatics $h [electronic resource] : $b 16th International Conference, BI 2023, Hoboken, NJ, USA, August 1-3, 2023 : proceedings / $c edited by Feng Liu ... [et al.].
246 3 $a BI 2023
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2023.
300 $a xiii, 479 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 13974
490 1 $a Lecture notes in artificial intelligence
505 0 $a Cognitive and Computational Foundations of Brain Science: Fusing Structural and Functional Connectivity using Disentangled VAE for Detecting MCI -- Modulation of Beta Power as a Function of Attachment Style and Feedback Valence -- Harnessing the Potential of EEG in Neuromarketing with Deep Learning and Riemannian Geometry -- A Model of the Contribution of Interneuron Diversity to Recurrent Network Oscillation Generation and Information Coding -- Measuring Stimulus-Related Redundant and Synergistic Functional Connectivity with Single Cell Resolution in Auditory Cortex -- Fusing Simultaneously Acquired EEG and fMRI via Hierarchical Deep Transcoding -- Investigations of Human Information Processing Systems: Decoding Emotion Dimensions Arousal and Valence Elicited on EEG Responses to Videos and Images: A Comparative Evaluation -- Stabilize Sequential Data Representation via Attractor Module -- Investigating the Generative Dynamics of Energy-Based Neural Networks -- Exploring Deep Transfer Learning Ensemble for Improved Diagnosis and Classification of Alzheimer's Disease -- Brain Big Data Analytics, Curation and Management: Effects of EEG Electrode Numbers on Deep Learning-Based Source Imaging -- Graph Diffusion Reconstruction Model for Addictive Brain-Network Computing -- MR Image Super-Resolution using Wavelet Diffusion for Predicting Alzheimer's Disease -- Classification of Event-Related Potential Signals with a Variant of UNet Algorithm using a Large P300 Dataset -- Dyslexia Data Consortium Repository: A Data Sharing and Delivery Platform for Research -- Conversion from Mild Cognitive Impairment to Alzheimer's Disease: A Comparison of Tree-based Machine Learning Algorithms for Survival Analysis -- Predicting Individual Differences from Brain Responses to Music: A Comparison of Functional Connectivity Measure -- Multiplex Temporal Networks for Rapid Mental Workload Classification -- Super-Resolution MRH Reconstruction for Mouse Models -- Bayesian Time Series Classifier for Decoding Simple Visual Stimuli from Intracranial Activity -- Variability of Non-parametric HRF in Interconnectedness and its Association in Deriving Resting State Network -- BrainSegNeT: A Lightweight Brain Tumor Segmentation Model based on U-Net and Progressive Neuron Expansion -- Improving Prediction Quality of Face Image Preference using Combinatorial Fusion Algorithm -- MMDF-ESI: Multi-Modal Deep Fusion of EEG and MEG for Brain Source Imaging -- Rejuvenating Classical Source Localization Methods with Spatial Graph Filters -- Prediction of Cannabis Addictive Patients with Graph Neural Networks -- Unsupervised Sparse-view Backprojection via Convolutional and Spatial Transformer Networks -- Latent Neural Source Recovery via Transcoding of Simultaneous EEG-fMRI -- Informatics Paradigms for Brain and Mental Health Research: Increasing the Power of Two-Sample T-Tests in Health Psychology using a Compositional Data Approach -- Estimating Dynamic Posttraumatic Stress Symptom Trajectories with Functional Data Analysis -- Comparison Between Explainable AI Algorithms for Alzheimer's Disease Prediction Using EfficientNet Models -- Social and Non-social Reward Learning Contexts for Detection of Major Depressive Disorder using EEG: A Machine Learning Approach -- Transfer Learning-Assisted DementiaNet: A Four Layer Deep CNN for Accurate Alzheimer's Disease Detection from MRI Images -- Multimodal Approaches for Alzheimer's Detection Using Patients' Speech and Transcript -- Brain-Machine Intelligence and Brain-Inspired Computing -- Exploiting Approximate Joint Diagonalization for Covariance Estimation in Imagined Speech Decoding -- Automatic Sleep-Wake Scoring with Optimally Selected EEG Channels from High-Density EEG -- EEG Source Imaging of Hand Movement-Related Areas: An Evaluation of the Reconstruction Accuracy with Optimized Channels -- Bagging the Best: A Hybrid SVM-KNN Ensemble for Accurate and Early Detection of Alzheimer's and Parkinson's Diseases -- Roe: A Computational-Efficient Anti-Hallucination Fine-Tuning Technology for Large Language Model Inspired by Human Learning Process -- The 5th International Workshop on Cognitive Neuroscience of Thinking and Reasoning: Brain Intervention Therapy Dilemma: Functional Recovery versus Identity.
520 $a This book constitutes the proceedings of the 16th International Conference on Brain Informatics, BI 2023, which was held in Hoboken, NJ, USA, during August 1-3, 2023. The 40 full papers presented in this book were carefully reviewed and selected from 101 submissions. The papers are divided into the following topical sections: cognitive and computational foundations of brain science; investigations of human Information processing systems; brain big data analytics, curation and management; informatics paradigms for brain and mental health research; brain-machine intelligence and brain-inspired computing; and the 5th international workshop on cognitive neuroscience of thinking and reasoning.
650 0 $a Neural networks (Computer science) $3 181982
650 0 $a Human information processing $v Congresses. $3 450994
650 0 $a Artificial intelligence $x Medical applications $v Congresses. $3 442992
650 1 4 $a Artificial Intelligence. $3 212515
650 2 4 $a Computer Application in Social and Behavioral Sciences. $3 913134
650 2 4 $a Computers and Education. $3 274532
650 2 4 $a Computer Engineering and Networks. $3 913124
700 1 $a Liu, Feng. $3 522549
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in computer science ; $v 4891. $3 383229
830 0 $a Lecture notes in artificial intelligence. $3 822012
856 4 0 $u https://doi.org/10.1007/978-3-031-43075-6
950 $a Computer Science (SpringerNature-11645)