Results 211 to 220 of about 259,715 (355)

Adaptive Denoising of Event-Related Functional Magnetic Resonance Imaging Data Using Spectral Subtraction [PDF]

, 2004
Yasser M. Kadah
openalex   +1 more source

Enhancing neural signal quality: a spike-denoising model with BiLSTM and attention mechanism. [PDF]

Brain Inform
Xu X, Chen N, Deng Y, Shen T, Wei N, Yu S, Zhang L.   +6 more
europepmc   +1 more source

Inverse Design of Alloys via Generative Algorithms: Optimization and Diffusion within Learned Latent Space

Advanced Intelligent Discovery, EarlyView.
This work presents a novel generative artificial intelligence (AI) framework for inverse alloy design through operations (optimization and diffusion) within learned compact latent space from variational autoencoder (VAE). The proposed work addresses challenges of limited data, nonuniqueness solutions, and high‐dimensional spaces.
Mohammad Abu‐Mualla, Ellis Crabtree, Fredrick Michael, Yayue Pan, Jida Huang   +4 more
wiley   +1 more source

Denoising of human speech using combined acoustic and EM sensor signal processing

, 2002
Lawrence C. Ng, Gregory C. Burnett, J. F. Holzrichter, Todd J. Gable   +3 more
openalex   +2 more sources

Wavelet-based denoising by customized thresholding [PDF]

, 2004
Byung-Jun Yoon, P. P. Vaidyanathan
openalex   +1 more source

Assessment of an unsupervised denoising approach based on Noise2Void in digital mammography. [PDF]

Sci Rep
Angelone F, Franco A, Ponsiglione AM, Ricciardi C, Belfiore MP, Gatta G, Grassi R, Sansone M, Amato F.   +8 more
europepmc   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source

<title>Denoising 3D models with attributes using soft thresholding</title> [PDF]

, 2004
Michael M. Roy, Sebti Foufou, Frédéric Truchetet   +2 more
openalex   +1 more source

Noise-augmented deep denoising: A method to boost CT image denoising networks. [PDF]

Med Phys
Kristof G, Eulig E, Kachelrieß M.
europepmc   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source