Advanced Intelligent Discovery, EarlyView.Deep learning‐based denoising models are applied to DNA data storage systems to enhance error reduction and data fidelity. By integrating DnCNN with DNA sequence encoding methods, the study demonstrates significant improvements in image quality and correction of substitution errors, revealing a promising path toward robust and efficient DNA‐based ...
Seongjun Seo +5 more
wiley +1 more source
Evaluating the impact of deep learning-based image denoising on low-dose CT for lung cancer screening. [PDF]
J Appl Clin Med PhysChen SS, Liu HH, Yang CC.
europepmc +1 more source
, 2020 Šiame darbe analizavome hiperspektrinius vaizdus, hiperspektrinias vaizdavimo technologijas ir triukšmo kilmę hiperspektriniuose vaizduose. Mes ištyrėme ir įgyvendinome kelis HSI triukšmo vertinimo metodus: koreliacijos koeficientų suradimo metodikas (R1 ir R2) ir tiesinės regresijos metodikas (LMLSD ir SSDC).
openaire +1 more source
Harnessing Digital Microstructure for Simulation‐Guided Optimization of Permanent Magnets
Advanced Intelligent Discovery, EarlyView.An experimental‐to‐computational workflow is presented that transforms experimental 3D focused ion beam‐scanning electron microscopy data into a simulation‐ready digital microstructure for multiphase functional materials. Using heavy‐rare‐earth‐free Nd–Fe–B magnets as a model system, the approach quantifies grain connectivity across complex secondary ...
Nikita Kulesh +4 more
wiley +1 more source
LeqMod: Adaptable Lesion-Quantification-Consistent Modulation for Deep Learning Low-Count PET Image Denoising. [PDF]
IEEE Trans Med ImagingXia M +11 more
europepmc +1 more source
Majority‐Voting Overlapping Method for Error Correction in DNA Data Storage
Advanced Intelligent Discovery, EarlyView.We propose an overlapping‐based majority‐voting method for DNA data storage error correction. By aligning multiple reads and choosing the most frequent base per position, it suppresses substitution errors without prior models. Validated on synthetic and real sequencing data, it achieves high‐fidelity, scalable, and cost‐effective reconstruction ...
Thi Bich Ngoc Nguyen +5 more
wiley +1 more source
BDNet: A Real-Time Biomedical Image Denoising Network with Gradient Information Enhancement Loss. [PDF]
Biosensors (Basel)Shi L +7 more
europepmc +1 more source
An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting
Advanced Intelligent Discovery, EarlyView.Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto +5 more
wiley +1 more source
Noise-augmented deep denoising: A method to boost CT image denoising networks. [PDF]
Med PhysKristof G, Eulig E, Kachelrieß M.
europepmc +1 more source
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
Advanced Intelligent Discovery, EarlyView.The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source