Results 101 to 110 of about 792,416 (284)

Residual Forward-Subtracted U-Shaped Network for Dynamic and Static Image Restoration

open access: yesIEEE Access, 2020
Advanced image sensors with high resolution are now being developed for specially purposed electro-optical systems, with research focused on robust image quality performance in terms of super resolution and noise removal under various environmental ...
Ho Min Jung   +2 more
doaj   +1 more source

Overview of molecular signatures of senescence and associated resources: pros and cons

open access: yesFEBS Open Bio, EarlyView.
Cells can enter a stress response state termed cellular senescence that is involved in various diseases and aging. Detecting these cells is challenging due to the lack of universal biomarkers. This review presents the current state of senescence identification, from biomarkers to molecular signatures, compares tools and approaches, and highlights ...
Orestis A. Ntintas   +6 more
wiley   +1 more source

GRIG: Data-efficient generative residual image inpainting

open access: yesComputational Visual Media
Image inpainting is the task of filling in missing or masked regions of an image with semantically meaningful content. Recent methods have shown significant improvement in dealing with large missing regions.
Wanglong Lu   +7 more
doaj   +1 more source

Enzymatic degradation of biopolymers in amorphous and molten states: mechanisms and applications

open access: yesFEBS Open Bio, EarlyView.
This review explains how polymer morphology and thermal state shape enzymatic degradation pathways, comparing amorphous and molten biopolymer structures. By integrating structure–reactivity principles with insights from thermodynamics and enzyme engineering, it highlights mechanisms that enable efficient polymer breakdown.
Anđela Pustak, Aleksandra Maršavelski
wiley   +1 more source

Residual Reinforcement Learning Enhanced With Unsuccessful Episode Buffer

open access: yesIEEE Open Journal of the Computer Society
Reinforcement learning (RL) agents have proven to be highly effective in many control domains; however, despite their generally promising performance, they may still encounter difficulties in certain challenging scenarios.To address this limitation, we ...
Peter Farkas, Tamas Becsi, Szilard Aradi
doaj   +1 more source

Semantic Residual Prompts for Continual Learning

open access: yes
Prompt-tuning methods for Continual Learning (CL) freeze a large pre-trained model and train a few parameter vectors termed prompts. Most of these methods organize these vectors in a pool of key-value pairs and use the input image as query to retrieve the prompts (values).
Martin Menabue   +6 more
openaire   +3 more sources

Applicability of mitotic figure counting by deep learning: a development and pan‐cancer validation study

open access: yesFEBS Open Bio, EarlyView.
In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes   +32 more
wiley   +1 more source

Digital twins to accelerate target identification and drug development for immune‐mediated disorders

open access: yesFEBS Open Bio, EarlyView.
Digital twins integrate patient‐derived molecular and clinical data into personalised computational models that simulate disease mechanisms. They enable rapid identification and validation of therapeutic targets, prediction of drug responses, and prioritisation of candidate interventions.
Anna Niarakis, Philippe Moingeon
wiley   +1 more source

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah   +7 more
wiley   +1 more source

A Parallel Image Denoising Network Based on Nonparametric Attention and Multiscale Feature Fusion

open access: yesSensors
Convolutional neural networks have achieved excellent results in image denoising; however, there are still some problems: (1) The majority of single-branch models cannot fully exploit the image features and often suffer from the loss of information.
Jing Mao   +3 more
doaj   +1 more source

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