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The elliptic net algorithm revisited
Efficient implementation of pairings is a fundamental ingredient in pairing-based cryptographic protocols. The Elliptic Net algorithm is an...
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2MGAS-Net: multi-level multi-scale gated attentional squeezed network for polyp segmentation
Accurate segmentation of colon polyps in endoscopic images is crucial for early colorectal cancer diagnosis and treatment planning. However,...
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MRI Brain tumor segmentation and classification with improved U-Net model
Brain tumors are among the deadliest diseases in the world. Early diagnosis thereby improves the patient's prospects and likelihood of recovery. It...
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Colonoscopy Polyp Detection Using Bi-Directional Conv-LSTM U-Net with Densely Connected Convolution
Several researchers have focused in recent years on improving the efficiency of abdominal diagnostics by segmenting colonoscopy images with machine...
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MBA-Net: multi-branch attention network for occluded person re-identification
Occluded person re-identification (ReID) aims to retrieve the same pedestrian from partially occluded pedestrian images across non-overlap**...
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Automatic skin lesion segmentation using attention residual U-Net with improved encoder-decoder architecture
The automatic segmentation of skin lesions in dermoscopic images is a challenging task due to the presence of artifacts, small lesion sizes, and low...
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A multi-frame sparse self-learning PWC-Net for motion estimation in satellite video scenes
Motion estimation is an important approach to acquiring motion information of all targets in satellite video while it provides the ability to...
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Hir-net: a simple and effective heterogeneous image restoration network
Image restoration refers to restoring the original image as much as possible from the damaged or degraded image. In recent years, deep learning-based...
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The nnU-Net based method for automatic segmenting fetal brain tissues
The magnetic resonance (MR) images of fetuses make it possible for doctors to detect out pathological fetal brains in early stages. Brain tissue...
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TRCA-Net: stronger U structured network for human image segmentation
Human image segmentation has been a practical and active research topic due to its wide range of potential application. There are some previous...
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FRR-NET: a fast reparameterized residual network for low-light image enhancement
Low-light image enhancement algorithm is an important branch in the field of image enhancement algorithms. To solve the problem of severe feature...
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HDUD-Net: heterogeneous decoupling unsupervised dehaze network
Haze reduces the imaging effectiveness of outdoor vision systems, significantly degrading the quality of images; hence, reducing haze has been a...
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ALP-Net: a segmentation-free approach for license plate recognition in unconstrained scenarios
License plate recognition technology is of paramount importance in intelligent transportation. While ideal scenario license plate recognition...
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RT-Net: Region-Enhanced Attention Transformer Network for Polyp Segmentation
Colonic polyps are highly correlated with colorectal cancer. Prevention of colorectal cancer is the detection and removal of polyps in the early...
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Scalable model for segmenting Cells’ Nuclei using the U-NET architecture
Medical image segmentation significantly influences medicine for diagnostic purposes where higher precision and accuracy are demanded. One of the...
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WHO-YOLO NET: soil prediction and classification based on YOLOV3 with whale optimization
Soil prediction techniques help to determine whether a particular crop will grow in a given area. The use of deep learning algorithms with complex...
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Hierarchical pose net: spatial hierarchical body tree driven multi-person pose estimation
In this paper, we explore multi-level semantic information of human body structure and propose a paradigm for bottom-up multi-person pose estimation....
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SI-Net: spatial interaction network for deepfake detection
As manipulated faces become more realistic and indistinguishable, there is a high demand for efficiently and accurately detecting deepfakes. Existing...
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Toward enhancing concrete crack segmentation accuracy under complex scenarios: a novel modified U-Net network
Convolutional neural networks (CNNs) have demonstrated promising accuracy in segmenting concrete cracks under controlled conditions. However, these...
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ES-Net: Unet-based model for the semantic segmentation of Iris
The segmentation of the iris is crucial and holds great importance within the medical image recognition area. Researchers have introduced many...
