the proceedings contain 179 papers. the topics discussed include: evolving product unit neural networks with particle swarm optimization;a method of image processing algorithm evaluation based on orthogonal experiment...
ISBN:
(纸本)9780769538839
the proceedings contain 179 papers. the topics discussed include: evolving product unit neural networks with particle swarm optimization;a method of image processing algorithm evaluation based on orthogonal experimental design;a convenient multi-camera self-calibration method based on human body motion analysis;degradation process simulation model for image enhancement;blind source separation based digital color image-adaptive watermarking;adaptive interpolation/extrapolation and motion vector processing method for frame rate up conversion;a self-adapting fast reconstruction method for high resolution images in cone beam CT;adaptive non-local means denoising algorithm for cone-beam computed tomography projection images;robot body guided camera calibration:calibration using an arbitrary circle;reduced reference image quality assessment based on contourlet domain and natural image statistics;and real-time camera pose estimation based on multiple planar markers.
the proceedings contain 57 papers. the topics discussed include: precision inspection and evaluation system for paper packaging of cigarettes;a lightweight network for violence detection;micro-expression detection bas...
ISBN:
(纸本)9781450395465
the proceedings contain 57 papers. the topics discussed include: precision inspection and evaluation system for paper packaging of cigarettes;a lightweight network for violence detection;micro-expression detection based on action units and multi-region feature fusion;multi-scale semantic representation and supervision for remote sensing change detection;cost-effective video-based poor repertoire detection for preterm infant general movement analysis;image inpainting based on edge features and attention mechanism;spatial non-cooperative target point cloud reconstruction;fast graph-based binary classifier learning via further relaxation of semi-definite relaxation;research on handwritten digital image recognition model based on deep learning and construction of browser service platform;analysis of eyebrow motion for micro-expression recognition;and features calculation of closed curve and its application in leaf discrimination.
the proceedings contain 15 papers. the topics discussed include: development of the logic programming approach to the intelligent monitoring of anomalous human behaviour;location of pupil contour by Hough transform of...
ISBN:
(纸本)9789897580949
the proceedings contain 15 papers. the topics discussed include: development of the logic programming approach to the intelligent monitoring of anomalous human behaviour;location of pupil contour by Hough transform of connectivity components;testing an image mining approach to obtain pressure ulcers stage and texture;on image representing in image analysis;a variational method to remove the combination of Poisson and Gaussian noises;PRIAR using a graph segmentation method;virtual immersive environments for underwater archaeological exploration;current trends in mathematical image analysis - a survey;human pose estimation in video via MCMC sampling;signal processing for underwater archaeology;experimenting an embedded-sensor network for early warning of natural risks due to fast failures along railways;selective use of optimal image resolution for depth from multiple motions based on gradient scheme;and blood flow prediction and visualization within the aneurysm of the middle cerebral artery after surgical treatment.
the proceedings contain 35 papers. the topics discussed include: data-driven approach for generating colormaps of scientific simulation data;a 3D-shockwave volume rendering algorithm based on feature boundary detectio...
ISBN:
(纸本)9789898704214
the proceedings contain 35 papers. the topics discussed include: data-driven approach for generating colormaps of scientific simulation data;a 3D-shockwave volume rendering algorithm based on feature boundary detection;using reorderable matrices to compare risk curves of representative models in oil reservoir development and management activities;laser spot detection and characteristic analysis in plasma interaction simulation;hybrid sort a pattern-focused matrix reordering approach based on classification;data interpolation based on contextual analysis for generating tomographic images in concrete specimen;graphical user interface personalization: user study of image frequency preferences;evaluation of color spaces for unsupervised and deep learning skin lesion segmentation;and repeated pattern extraction with knowledge-based attention and semantic embeddings.
the proceedings contain 21 papers. the special focus in this conference is on Advances in Simplifying Medical Ultrasound. the topics include: Do High-Performance image-to-image Translation Networks Enable the Discover...
ISBN:
(纸本)9783031736469
the proceedings contain 21 papers. the special focus in this conference is on Advances in Simplifying Medical Ultrasound. the topics include: Do High-Performance image-to-image Translation Networks Enable the Discovery of Radiomic Features? Application to MRI Synthesis from Ultrasound in Prostate Cancer;PHOCUS: Physics-Based Deconvolution for Ultrasound Resolution Enhancement;PIPsUS: Self-supervised Point Tracking in Ultrasound;structure-aware World Model for Probe Guidance via Large-scale Self-supervised Pre-train;an Evaluation of Low-Cost Hardware on 3D Ultrasound Reconstruction Accuracy;Learning to Match 2D Keypoints Across Preoperative MR and Intraoperative Ultrasound;automatic Facial Axes Standardization of 3D Fetal Ultrasound images;C-TRUS: A Novel Dataset and Initial Benchmark for Colon Wall Segmentation in Transabdominal Ultrasound;label Dropout: Improved Deep Learning Echocardiography Segmentation Using Multiple Datasets with Domain Shift and Partial Labelling;introducing Anatomical Constraints in Mitral Annulus Segmentation in Transesophageal Echocardiography;interactive Segmentation Model for Placenta Segmentation from 3D Ultrasound images;Enhanced Uncertainty Estimation in Ultrasound image Segmentation with MSU-Net;multi-site Class-Incremental Learning with Weighted Experts in Echocardiography;Masked Autoencoders for Medical Ultrasound Videos Using ROI-Aware Masking;uncertainty-Based Multi-modal Learning for Myocardial Infarction Diagnosis Using Echocardiography and Electrocardiograms;fetal Ultrasound Video Representation Learning Using Contrastive Rubik’s Cube Recovery;LoRIS - Weakly-Supervised Anomaly Detection for Ultrasound images;unsupervised Detection of Fetal Brain Anomalies Using Denoising Diffusion Models;diffusion Models for Unsupervised Anomaly Detection in Fetal Brain Ultrasound.
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
A GAN-based image recognition algorithm is presented to solve these problems. Firstly, the GAN frame is composed of a generator and a discriminator. the generator can produce real images or remove noise by learning th...
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the automatic development of meaningful, detailed textual descriptions for supplied images is a difficult task in the fields of computer vision and natural language processing. As a result, an AI-powered image caption...
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the automatic development of meaningful, detailed textual descriptions for supplied images is a difficult task in the fields of computer vision and natural language processing. As a result, an AI-powered image caption generator can be incredibly useful for producing captions. In this study, we present a unique method for creating picture captions utilizing an attention mechanism that concentrates on pertinent areas of the image while it creates captions. On benchmark datasets, our model, which uses deep neural networks to extract picture attributes and produce captions, obtains state-of-the-art results, confirming the effectiveness of the attention mechanism in raising the caliber of the generated captions. We also offer a thorough evaluation of the performance of our approach and talk about potential future directions for enhancing image caption generation.
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