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Evaluation of sparsity metrics and evolutionary algorithms applied for normalization of H&E histological images
Color variations in H&E histological images can impact the segmentation and classification stages of computational systems used for cancer diagnosis....
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Image enhancement with bi-directional normalization and color attention-guided generative adversarial networks
The image enhancement aims to improve the quality of images from contrast, detail, and color perspectives by adjusting the color of an image to match...
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A new complete color normalization method for H&E stained histopatholgical images
The popularity of digital histopathology is growing rapidly in the development of computer aided disease diagnosis systems. However, the color...
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A Robust BKSVD Method for Blind Color Deconvolution and Blood Detection on H &E Histological Images
Hematoxylin and Eosin (H &E) color variation between histological images from different laboratories degrades the performance of Computer-Aided...
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Tackling Mitosis Domain Generalization in Histopathology Images with Color Normalization
In this paper, we propose a method for mitosis detection in histopathology images in an unsupervised domain adaptation setting. Our method is a...
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Improved two-stage image inpainting with perceptual color loss and modified region normalization
In this work, we propose a two-stage architecture to perform image inpainting from coarse to fine. The framework extracts advantages from different...
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Regional realness-aware generative adversarial networks for stain normalization
Stain normalization is the standardization of the color appearance and has been commonly used in computer-aided diagnosis (CAD) systems. Recently,...
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A Fast Stain Normalization Network for Cervical Papanicolaou Images
The domain shift between different styles of stain images greatly challenges the generalization of computer-aided diagnosis (CAD) algorithms. To...
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Content-based image retrieval with fuzzy clustering for feature vector normalization
In content-based image retrieval using combine multiple low-level features or deep learning features, data imbalance after normalization often...
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HSSAN: hair synthesis with style-guided spatially adaptive normalization on generative adversarial network
Hair synthesis plays a crucial role in generating facial images, but the complex textures and varied shapes of hair create obstacles in creating...
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KL Regularized Normalization Framework for Low Resource Tasks
Large pretrained models, such as Bert, GPT, and Wav2Vec, have demonstrated great potential for learning representations that are transferable to a...
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Face illumination normalization based on generative adversarial network
Face recognition technology has been widely used in the field of artificial intelligence. The technology needs to be carried out normally under the...
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Domain-Conditioned Normalization for Test-Time Domain Generalization
Domain generalization aims to train a robust model on multiple source domains that generalizes well to unseen target domains. While considerable...
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Self-attentive Adversarial Stain Normalization
Hematoxylin and Eosin (H&E) stained Whole Slide Images (WSIs) are utilized for biopsy visualization-based diagnostic and prognostic assessment of...
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A novel enhanced normalization technique for a mandible bones segmentation using deep learning: batch normalization with the dropout
Several cases of oral and maxillofacial surgery require 3D virtual surgical planning, which is essential for craniofacial tumor resection and flap...
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PointSGLN: a novel point cloud classification network based on sampling grou** and local point normalization
The point cloud data structure is characterized by disorder and spatial irregularity, which makes it impossible to apply 2D convolutional neural...
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Deep snapshot HDR imaging using multi-exposure color filter array
In this paper, we propose a deep snapshot high dynamic range (HDR) imaging framework that can effectively reconstruct an HDR image from the RAW data...
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Towards Defending Multiple \(\ell _p\)-Norm Bounded Adversarial Perturbations via Gated Batch Normalization
There has been extensive evidence demonstrating that deep neural networks are vulnerable to adversarial examples, which motivates the development of...
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Spectral normalization and dual contrastive regularization for image-to-image translation
Existing image-to-image (I2I) translation methods achieve state-of-the-art performance by incorporating the patch-wise contrastive learning into...
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Lightweight real-time lane detection algorithm based on ghost convolution and self batch normalization
A lane detection algorithm based on lane shape prediction with transformers (LSTR) is designed to address the problems of a large number of feature...
