the proceedings contain 131 papers. the topics discussed include: progressive semantic consistency towards unsupervised cross-modality medical image segmentation;innovative research on image dehazing by integrating mu...
ISBN:
(纸本)9798331530334
the proceedings contain 131 papers. the topics discussed include: progressive semantic consistency towards unsupervised cross-modality medical image segmentation;innovative research on image dehazing by integrating multi-dimensional attention and multi-model fusion MixdehazeNet;a hybrid CNN-LSTM architecture for enhanced music genre classification;predicting liquidity coverage ratio with gated recurrent units: a deep learning model for risk management;research on a sentiment analysis model based on RoBERTa integrating bidirectional gated recurrent networks and multi-head attention;improving aircraft engine remaining useful life prediction scheme based on handcrafted features and neural network integration;and rolling bearing fault diagnosis algorithm based on RCMSDE fusion transfer learning.
the proceedings contain 125 papers. the topics discussed include: research on contrastive image classification algorithm based on scalable self-attention;research on intelligent transportation algorithms based on arti...
ISBN:
(纸本)9781510680258
the proceedings contain 125 papers. the topics discussed include: research on contrastive image classification algorithm based on scalable self-attention;research on intelligent transportation algorithms based on artificial intelligence;prediction of aero engine residual life based on chaotic genetic algorithm to optimize TCN network;construction of a power quality and electrical equipment knowledge graph for equipment status assessment;improved multi-scale convolutional neural network about image defogging method;power equipment target detection algorithm based on improved YOLOV7;enhancing helmet and cigarette detection in electricity power construction based onYolov5s-I algorithm;privacy efficient federal learning approach for smart security;and obstruction detection and recovery in weather radar images using deep learning.
the proceedings contain 9 papers. the topics discussed include: categorization of post-sale automotive customer feedback using natural language processing;improving service chatbot using semantic based short-term memo...
ISBN:
(纸本)9798350375763
the proceedings contain 9 papers. the topics discussed include: categorization of post-sale automotive customer feedback using natural language processing;improving service chatbot using semantic based short-term memory;design of pig inventory and abnormality monitoring system based on livestock Internet of things orbital inspection robot;a study on the cognition of symbolic imagery in computer graphics synthetic imagery;and breaking the validation trade-off in topic extraction: a bi-objective metaheuristic model for labelling short-text clusters and an application on AirBnB Tokyo reviews.
the proceedings contain 23 papers. the special focus in this conference is on Skin Imaging Collaboration, Interpretability of machine Intelligence in Medical Image Computing, Embodied AI and Robotics for Healthcare Wo...
ISBN:
(纸本)9783031776090
the proceedings contain 23 papers. the special focus in this conference is on Skin Imaging Collaboration, Interpretability of machine Intelligence in Medical Image Computing, Embodied AI and Robotics for Healthcare Workshop and MICCAI Workshop on Distributed, Collaborative and Federated learning. the topics include: DeCaF 2024 Preface;i2M2Net: Inter/Intra-modal Feature Masking Self-distillation for Incomplete Multimodal Skin Lesion Diagnosis;from Majority to Minority: A Diffusion-Based Augmentation for Underrepresented Groups in Skin Lesion Analysis;segmentation Style Discovery: application to Skin Lesion Images;a Vision Transformer with Adaptive Cross-Image and Cross-Resolution Attention;lesion Elevation Prediction from Skin Images Improves Diagnosis;DWARF: Disease-Weighted Network for Attention Map Refinement;PIPNet3D: Interpretable Detection of Alzheimer in MRI Scans;Detecting Unforeseen Data Properties with Diffusion Autoencoder Embeddings Using Spine MRI Data;interpretability of Uncertainty: Exploring Cortical Lesion Segmentation in Multiple Sclerosis;TextCAVs: Debugging Vision Models Using Text;evaluating Visual Explanations of Attention Maps for Transformer-Based Medical Imaging;Exploiting XAI Maps to Improve MS Lesion Segmentation and Detection in MRI;EndoGS: Deformable Endoscopic Tissues Reconstruction with Gaussian Splatting;VISAGE: Video Synthesis Using Action Graphs for Surgery;a Review of 3D Reconstruction Techniques for Deformable Tissues in Robotic Surgery;SurgTrack: CAD-Free 3D Tracking of Real-World Surgical Instruments;MUTUAL: Towards Holistic Sensing and Inference in the Operating Room;Complex-Valued Federated learning with Differential Privacy and MRI applications;enhancing Privacy in Federated learning: Secure Aggregation for Real-World Healthcare applications;federated Impression for learning with Distributed Heterogeneous Data;A Federated learning-Friendly Approach for Parameter-Efficient Fine-Tuning of SAM in 3D Segmentation;probing the Effic
the proceedings contain 21 papers. the special focus in this conference is on Longitudinal Disease Tracking and Modeling with Medical Images and Data. the topics include: Disease Progression Modelling and Stratif...
ISBN:
(纸本)9783031845246
the proceedings contain 21 papers. the special focus in this conference is on Longitudinal Disease Tracking and Modeling with Medical Images and Data. the topics include: Disease Progression Modelling and Stratification for Detecting Sub-trajectories in the Natural History of Pathologies: application to Parkinson’s Disease Trajectory Modelling;back to the Future: Challenges of Sparse and Irregular Medical Image Time Series;Individualized Multi-horizon MRI Trajectory Prediction for Alzheimer’s Disease;towards Longitudinal Characterization of Multiple Sclerosis Atrophy Employing SynthSeg Framework and Normative Modeling;segHeD: Segmentation of Heterogeneous Data for Multiple Sclerosis Lesions with Anatomical Constraints;Longitudinal Segmentation of MS Lesions via Temporal Difference Weighting;registration of Longitudinal Liver Examinations for Tumor Progress Assessment;Tracking Lesion Evolution Using a Boundary Enhanced Approach for MS Change Segmentation (BEAMS);a Radiological-Based Coordinate System for the Human Body: A Proof-of-Concept;language Models Meet Anomaly Detection for Better Interpretability and Generalizability;A Diffusion Model Embedded WCSAU-Net for 3D MRI Brain Tumor Segmentation;predicting Human Brain States with Transformer;Cross-Modality Image Quality Prediction for Time-Resolved CT from Breathing Signals;RATNUS: Rapid, Automatic thalamic Nuclei Segmentation Using Multimodal MRI Inputs;HyperMM: Robust Multimodal learning with Varying-Sized Inputs;HEMIT: H&E to Multiplex-Immunohistochemistry Image Translation with Dual-Branch Pix2pix Generator;Physics-Informed Latent Diffusion for Multimodal Brain MRI Synthesis;medPromptX: Grounded Multimodal Prompting for Chest X-Ray Diagnosis;predicting Stroke through Retinal Graphs and Multimodal Self-supervised learning;multimodality for Diagnosis of Asian Choroidal Vasculopathy: Results from a Novel Dataset and Deep-learning Experiments;multimodality Frequency Feature Customized learning for Pediatric Ventricu
Withthe continuous development of artificial intelligence, machinelearning has shown great ability in classification and regression problems. For example, logistic regression, SVM methods, and neural networks are wi...
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this study leverages machinelearning models, including Logistic Regression, XGBoost, and Random Forest, to predict diabetes using BRFSS data. XGBoost emerged as the topperforming model, achieving an AUC of 0.83. Feat...
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Intelligent scheduling holds a significant position in modern manufacturing, becoming a challenging problem due to its complexity and multiple constraints. this study proposes a novel reinforcement learning approach t...
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In response to the problem of reduced performance of classification models due to label noise in real-world scenarios, this paper proposes a robust broad learning system that suppresses noise effectively and has param...
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