Recovering Badly Exposed Objects From Digital Photos Using Internet Images

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Attribute-based representations help machine learning models perform tasks based on human understandable concepts, allowing a closer human-machine collaboration. However, learning attributes that accurately reflect the content of an image is not always str ...

This paper describes the development of a novel medical x-ray imaging system adapted to the needs and constraints of low- and middle-income countries. The developed system is based on an indirect conversion chain: a scintillator plate produces visible ligh ...

Noise is an intrinsic part of any sensor and is present, in various degrees, in any content that has been captured in real life environments. In imaging applications, several pre- and post-processing solutions have been proposed to cope with noise in captu ...

Scene and reference results files for: "A Critical Comparison of Annual Glare Simulation Methods" Stephen Wasilewski, Jan Wienold, Marilyne Andersen 2022 Buildsim Nordic, Copenhagen Contents: 01-06*.tar.gz: reference simulation image archives, one ...

Due to the increasing number of pictures captured and stored every day by and on digital devices, lossy image compression has become inevitable to limit the needed storage requirement. As a consequence, these compression methods might introduce some visual ...

We present a pipeline for the automatic generation of digital twins of free-standing buildings for damage assessment. Our method takes multiple view images of the target building as input and processes them to produce a 3D model in levels of detail (LOD) f ...

Though museums are digitising their archives, online consultations remain low. New forms of engagement bring these digital memories to life and can support museums in maintaining and developing digital resources. Artificial Intelligence presents opportunit ...

During the Artificial Intelligence (AI) revolution of the past decades, deep neural networks have been widely used and have achieved tremendous success in visual recognition. Unfortunately, deploying deep models is challenging because of their huge model s ...

State-of-the-art 2D image compression schemes rely on the power of convolutional neural networks (CNNs). Although CNNs offer promising perspectives for 2D image compression, extending such models to omnidirectional images is not straightforward. First, omn ...

Recovering Badly Exposed Objects From Digital Photos Using Internet Images

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Attribute Prediction as Multiple Instance Learning

X-ray imaging detector for radiological applications adapted to the context and requirements of low- and middle-income countries

On combining denoising with learning-based image decoding

reference data for "A Critical Comparison of Annual Glare Simulation Methods"

Towards JPEG AIC part 3: visual quality assessment of high to visually lossless image coding

Digital twins for post-earthquake damage assessment of free-standing buildings including damage information

Poster World. Bespoke AI Meets Curator Expertise for Public Engagement

Improving the Training of Compact Neural Networks for Visual Recognition

OSLO: On-the-Sphere Learning for Omnidirectional Images and Its Application to 360-Degree Image Compression