Feature-based no-reference video quality assessment using Extra Trees

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Central aortic diastolic pressure decay time constant ( ) is according to the two-element Windkessel model equal to the product of total peripheral resistance (R) times total arterial compliance (C ). As such, it is related to arterial stiffness, which has ...

This paper presents a comparison of machine learning (ML) methods used for three-dimensional localization of partial discharges (PD) in a power transformer tank. The study examines ML and deep learning (DL) methods, ranging from support vector machines (SV ...

AIM: To characterise the corticoreticular pathway (CRP) in a case -control cohort of adolescent idiopathic scoliosis (AIS) patients using high -resolution slice -accelerated readoutsegmented echo -planar diffusion tensor imaging (DTI) to enhance the discri ...

Objective: This study aimed to evaluate the performances of quantitative ultrasound (QUS) for the detection and assessment of hepatic steatosis when implemented using an ultraportable ultrasound scanner. Methods: Seven established QUS parameters were inves ...

Herein, machine learning (ML) models using multiple linear regression (MLR), support vector regression (SVR), random forest (RF) and artificial neural network (ANN) are developed and compared to predict the output features viz. specific capacitance (Csp), ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

Background Socio-emotional difficulties often result from very preterm (VPT) birth. The amygdala's developmental trajectory, including its nuclei, has been recognized as a significant factor in observed difficulties. This study aims to assess the relations ...

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

Ultra-high performance fiber reinforced cementitious composite (UHPFRC) is a modern class of cementitious building materials. Because of its superior mechanical properties and durability, it is increasingly used globally to rehabilitate, strengthen and mod ...

We consider the problem of defining and fitting models of autoregressive time series of probability distributions on a compact interval of Double-struck capital R. An order-1 autoregressive model in this context is to be understood as a Markov chain, where ...

Video DeepFakes are fake media created with Deep Learning (DL) that manipulate a person’s expression or identity. Most current DeepFake detection methods analyze each frame independently, ignoring inconsistencies and unnatural movements between frames. Som ...

Breast cancer is a significant global health burden, causing a substantial number of deaths. Systemic metastatic tumour cell dissemination is a major cause of poor outcomes. Understanding the mechanisms underlying metastasis is crucial for effective interv ...

Context. The Euclid mission of the European Space Agency will perform a survey of weak lensing cosmic shear and galaxy clustering in order to constrain cosmological models and fundamental physics. Aims. We expand and adjust the mock Euclid likelihoods of t ...

Combining galaxy clustering information from regions of different environmental densities can help break cosmological parameter degeneracies and access non-Gaussian information from the density field that is not readily captured by the standard two-point c ...

Using batteries of visual tests, most studies have found that there are only weak correlations between performance levels of tests in healthy young adults. Factor analysis has confirmed these results. This means that a participant excelling in one test may ...

Point clouds are effective data structures for the rep- resentation of three-dimensional media and hence adopted in a wide range of practical applications. In many cases, the portrayed data is expected to be visualized by humans. After acquisition, point c ...

Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the pe ...

Background: A neurocognitive phenotype of post-COVID-19 infection has recently been described that is characterized by a lack of awareness of memory impairment (i.e., anosognosia), altered functional connectivity in the brain's default mode and limbic netw ...

We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

Feature-based no-reference video quality assessment using Extra Trees

Chattez avec Graph Search

Novel theory and potential applications of central diastolic pressure decay time constant

Partial discharge localization in power transformer tanks using machine learning methods

The hindbrain and cortico-reticular pathway in adolescent idiopathic scoliosis

Ultraportable Quantitative Ultrasound for Hepatic Steatosis Assessment

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Reliable data-driven decision-making through optimal transport

Amygdala volumes and associations with socio-emotional competencies in preterm youth: cross-sectional and longitudinal data

Random matrix methods for high-dimensional machine learning models

Influence of fiber orientation on the tensile behavior of UHPFRC and reinforced UHPFRC under static and fatigue loadings

On distributional autoregression and iterated transportation

Efficient Temporally-Aware DeepFake Detection using H.264 Motion Vectors

Unveiling breast cancer metastasis through an advanced X-ray imaging approach

Euclid: Validation of the MontePython forecasting tools

SUNBIRD : a simulation-based model for full-shape density-split clustering

Diving into the heterogeneity of the visual system

Towards a multiscale point cloud structural similarity metric

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

Acute TNF alpha levels predict cognitive impairment 6-9 months after COVID-19 infection

Bayes-optimal Learning of Deep Random Networks of Extensive-width