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Histopathological Stain Transfer using Style Transfer Network with Adversarial L…
Deep learning models that are trained on histopathological images obtained from a single lab and/or scanner give poor inference performance on images obtained from another scanner/lab with a different staining protocol. In recent years, there has bee...
Improved anomaly detection by training an autoencoder with skip connections on i…
In industrial vision, the anomaly detection problem can be addressed with an autoencoder trained to map an arbitrary image, i.e. with or without any defect, to a clean image, i.e. without any defect. In this approach, anomaly detection relies convent...
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Deep End-to-End Posterior ENergy (DEEPEN) for image recovery
Current end-to-end (E2E) and plug-and-play (PnP) image reconstruction algorithms approximate the maximum a posteriori (MAP) estimate but cannot offer sampling from the posterior distribution, like diffusion models. By contrast, it is challenging for...
Cupdate - A self-hosted service for Kubernetes and Docker to help keep container…
Hi there, r/selfhosted! I've been working on a service called Cupdate for a while. Cupdate automatically identifies container images in use in your Kubernetes cluster or on your Docker host. Cupdate ...
Unearthed Arcana: Mystic Subclasses
[https://media.dndbeyond.com/compendium-images/ua/mystic-subclasses/mrF6k4xf0yYFJL2m/UA2026-MysticSubclasses.pdf](https://media.dndbeyond.com/compendium-images/ua/mystic-subclasses/mrF6k4xf0yYFJL2m/UA...
Toyota Fortuner Legender 2026 Price, Features, Images, Specs
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C2P-GCN: Cell-to-Patch Graph Convolutional Network for Colorectal Cancer Grading
Graph-based learning approaches, due to their ability to encode tissue/organ structure information, are increasingly favored for grading colorectal cancer histology images. Recent graph-based techniques involve dividing whole slide images (WSIs) into...
Google tweaks image search and SafeSearch to show less explicit content
Points: 40 | Comments: 18 | Author: thejteam
HAWKEYE: Adversarial Example Detector for Deep Neural Networks
Adversarial examples (AEs) are images that can mislead deep neural network (DNN) classifiers via introducing slight perturbations into original images. Recent work has shown that detecting AEs can be more effective against AEs than preventing them fr...
Q-Hawkeye: Reliable Visual Policy Optimization for Image Quality Assessment
Image Quality Assessment (IQA) predicts perceptual quality scores consistent with human judgments. Recent RL-based IQA methods built on MLLMs focus on generating visual quality descriptions and scores, ignoring two key reliability limitations: (i) al...
Hawkeye: A PyTorch-based Library for Fine-Grained Image Recognition with Deep Le…
Fine-Grained Image Recognition (FGIR) is a fundamental and challenging task in computer vision and multimedia that plays a crucial role in Intellectual Economy and Industrial Internet applications. However, the absence of a unified open-source softwa...
Dickson Invariants in the image of the Steenrod Square
Let D_n be the Dickson invariant ring of F_2[X_1,...,X_n] acted by the general linear group GL(n,\F_2). In this paper, we provide an elementary proof of the conjecture by [Hung]: each element in D_n is in the image of the Steenrod square in F_2[X_1...
jkvor/s3-image-viewer
Web application for viewing a series of images stored in an Amazon S3 bucket. (⭐ 14)
AI tool generates high-quality images faster than state-of-the-art ...
Mar 21, 2025 · A hybrid AI approach known as hybrid autoregressive transformer can generate realistic images with the same or better quality than state-of-the-art diffusion models, but that runs about nine …
Free Meme Generator — Make Video, Image, and Text Memes …
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