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A CauchyTV non-convex regularization model for MRI reconstruction
In this paper, we study the non-convex regularization problem based on magnetic resonance imaging (MRI) reconstruction. In order to achieve high...
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Learnable Objective Image Function for Accelerated MRI Reconstruction
Magnetic Resonance Imaging (MRI) provides strong contrast for soft tissues but requires long acquisition times, oftentimes resulting in the motion...
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Self-supervised neural network-based endoscopic monocular 3D reconstruction method
Based on deep learning, monocular visual 3D reconstruction methods have been applied in various conventional fields. In the aspect of medical...
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Deep learning-based 3D reconstruction: a survey
Image-based 3D reconstruction is a long-established, ill-posed problem defined within the scope of computer vision and graphics. The purpose of...
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Robust fingerprint reconstruction using attention mechanism based autoencoders and multi-kernel autoencoders
AbstractFingerprint recognition technology is widely employed for identity verification and access control across diverse domains in which the...
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Learning Dynamic MRI Reconstruction with Convolutional Network Assisted Reconstruction Swin Transformer
Dynamic magnetic resonance imaging (DMRI) is an effective imaging tool for diagnosis tasks that require motion tracking of a certain anatomy. To...
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Soft threshold iteration-based anti-noise compressed sensing image reconstruction network
Optical images of artificial satellites can provide wide-range geographic information, but their large amount of information and severe noise...
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TopologyFormer: structure transformer assisted topology reconstruction for point cloud completion
Point cloud completion is a fundamental task to enhance the completeness and authenticity of point cloud data captured in the real world. Existing...
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Attention-based network for passive non-light-of-sight reconstruction in complex scenes
Passive non-line-of-sight (NLOS) reconstruction has received considerable success in diverse fields. However, the existing reconstruction methods...
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Anomaly detection for image data based on data distribution and reconstruction
Anomaly detection is a classical problem of identifying whether a query is an inlier or an outlier, with only inliers available during training....
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Addiction-related brain networks identification via Graph Diffusion Reconstruction Network
Functional magnetic resonance imaging (fMRI) provides insights into complex patterns of brain functional changes, making it a valuable tool for...
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Geometric constraints based 3D reconstruction method of tomographic SAR for buildings
The mainstream methods of tomographic synthetic aperture radar (tomoSAR) 3D reconstruction are usually realized by processing the registered 2D SAR...
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Adaptive fish school search optimized resnet for multi-view 3D objects reconstruction
Reconstruction of multi-view 3-dimensional images is essential in robotics and computer vision to obtain an accurate 3-dimensional representation of...
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3D reconstruction method based on N-step phase unwrap**
Reducing the number of images in fringe projection profilometry has emerged as a significant research focus. Traditional temporal phase unwrap**...
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Joint reconstruction and deidentification for mobile identity anonymization
The growing use of deep learning methods in various applications has raised concerns about privacy, as these methods heavily rely on large-scale...
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Turna: a control flow graph reconstruction tool for RISC-V architecture
A control flow graph (CFG) is a type of directed graph that shows the execution paths of the programs. It is a mathematical structure that is...
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Infrared image super-resolution reconstruction based on residual fast fourier transform
Infrared images have been widely used in military, civilian, and industrial fields. Due to the inherent limitations of sensors, infrared images...
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A systematic literature review of generative adversarial networks (GANs) in 3D avatar reconstruction from 2D images
The rapid advancement of machine learning and computer vision has paved the way for significant processes in 3D avatar reconstruction from 2D images....
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Color image-guided very low-resolution depth image reconstruction
Deep learning-based image super-resolution research allows reconstruction of detailed images from low-resolution images in a short time. However, the...
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Adaptive radio map reconstruction via adversarial wireless fingerprint learning
Wi-Fi signals play an essential role in indoor location-based services. However, the Wi-Fi radio map is vulnerable to deployment changes, leading to...
