13 Result(s)
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Chapter and Conference Paper
PE-MED: Prompt Enhancement for Interactive Medical Image Segmentation
Interactive medical image segmentation refers to the accurate segmentation of the target of interest through interaction (e.g., click) between the user and the image. It has been widely studied in recent years...
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Chapter and Conference Paper
Envisioning the Future Trends of Smart Assistive Devices to Support Activities of Daily Living for Older Adults with Disabilities
The elderly care industry will face significant pressure, especially the disabled older adults will be the crucial object of service and support. Older adults with a disability who have lost the ability to liv...
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Chapter and Conference Paper
Statistical Dependency Guided Contrastive Learning for Multiple Labeling in Prenatal Ultrasound
Standard plane recognition plays an important role in prenatal ultrasound (US) screening. Automatically recognizing the standard plane along with the corresponding anatomical structures in US image can not onl...
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Chapter and Conference Paper
Background Learnable Cascade for Zero-Shot Object Detection
Zero-shot detection (ZSD) is crucial to large-scale object detection with the aim of simultaneously localizing and recognizing unseen objects. There remain several challenges for ZSD, including reducing the am...
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Chapter and Conference Paper
Joint Graph Contextualized Network for Sequential Recommendation
Sequential recommendation aims to suggest items to users based on sequential dependencies. Graph neural networks (GNNs) are recently proposed to capture transitions of items by treating session sequences as gr...
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Chapter and Conference Paper
Convolutional Feature-Interacted Factorization Machines for Sparse Contextual Prediction
Factorization Machines (FMs) are extensively used for sparse contextual prediction tasks by modeling feature interactions. Despite successful application of FM and its abundant deep learning variants, these im...
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Chapter and Conference Paper
Auto-weighting for Breast Cancer Classification in Multimodal Ultrasound
Breast cancer is the most common invasive cancer in women. Besides the primary B-mode ultrasound screening, sonographers have explored the inclusion of Doppler, strain and shear-wave elasticity imaging to adva...
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Chapter and Conference Paper
Contrastive Rendering for Ultrasound Image Segmentation
Ultrasound (US) image segmentation embraced its significant improvement in deep learning era. However, the lack of sharp boundaries in US images still remains an inherent challenge for segmentation. Previous m...
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Chapter and Conference Paper
Automated Fetal Brain Extraction from Clinical Ultrasound Volumes Using 3D Convolutional Neural Networks
To improve the performance of most neuroimage analysis pipelines, brain extraction is used as a fundamental first step in the image processing. However, in the case of fetal brain development for routing clin...
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Chapter and Conference Paper
An Automated CNN-based 3D Anatomical Landmark Detection Method to Facilitate Surface-Based 3D Facial Shape Analysis
Maternal alcohol consumption during pregnancy can lead to a wide range of physical and neurodevelopmental problems, collectively known as fetal alcohol spectrum disorders (FASD). In many cases, diagnosis is h...
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Chapter and Conference Paper
Omni-Supervised Learning: Scaling Up to Large Unlabelled Medical Datasets
Two major bottlenecks in increasing algorithmic performance in the field of medical imaging analysis are the typically limited size of datasets and the shortage of expert labels for large datasets. This paper ...
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Chapter and Conference Paper
Video Quality Assessment Based on the Improved LSTM Model
With the development of computer and network technologies, video service and content will continue to dominate while comparing to all other applications. It is particularly important to build a real-time and e...
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Article
Automated sampling and control of gaseous simulations
In this work, we describe a method that automates the sampling and control of gaseous fluid simulations. Several recent approaches have provided techniques for artists to generate high-resolution simulations b...
