Results 91 to 100 of about 116,500 (328)

Large Scale Variational Bayesian Inference for Structured Scale Mixture Models [PDF]

, 2012
Natural image statistics exhibit hierarchical dependencies across multiple scales. Representing such prior knowledge in non-factorial latent tree models can boost performance of image denoising, inpainting, deconvolution or reconstruction substantially ...
Ko, Young Jun, Seeger, Matthias
core   +2 more sources

QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data

, 2017
Optical coherence tomography (OCT) enables high-resolution and non-invasive 3D imaging of the human retina but is inherently impaired by speckle noise.
A Ozcan, A Wong, H Salinas, J Cheng, J Duan, K Dabov, L Fang, M Pircher, MA Mayer, P Ochs, T Goldstein, T Köhler, W Choi   +12 more
core   +1 more source

TacScope: A Miniaturized Vision‐Based Tactile Sensor for Surgical Applications

Advanced Robotics Research, EarlyView.
TacScope is a compact, vision‐based tactile sensor designed for robot‐assisted surgery. By leveraging a curved elastomer surface with pressure‐sensitive particle redistribution, it captures high‐resolution 3D tactile feedback. TacScope enables accurate tumor detection and shape classification beneath soft tissue phantoms, offering a scalable, low‐cost ...
Md Rakibul Islam Prince, Sheeraz Athar, Pokuang Zhou, Yu She   +3 more
wiley   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Deep learning informed diffusion equation model for image denoising

IET Image Processing
Image denoising is one of the fundamental problems in image processing. Convolutional neural network (CNN) based denoising approaches have achieved better performance than traditional methods, such as STROLLR and BM3D.
Yao Li, Li Cheng, Zhichang Guo, Yuming Xing   +3 more
doaj   +1 more source

Smart REASSURED Sensors via Machine‐Augmented Printable On‐Paper Arrays

Advanced Sensor Research, EarlyView.
This perspective highlights the emerging role of pattern‐recognition, printable on‐paper sensor arrays for intelligent PoC diagnostics. It discusses how paper's inherent limitations can be overcome through surface modification and scalable printing, and how machine‐learning analysis of cross‐reactive arrays enables multiplexed, low‐cost, and REASSURED ...
Naimeh Naseri, Saba Ranjbar
wiley   +1 more source

Boosting of Denoising Effect with Fusion Strategy

Applied Sciences, 2020
Image denoising, a fundamental step in image processing, has been widely studied for several decades. Denoising methods can be classified as internal or external depending on whether they exploit the internal prior or the external noisy-clean image ...
Fangjia Yang, Shaoping Xu, Chongxi Li
doaj   +1 more source

Gaussian Priors for Image Denoising [PDF]

, 2018
This chapter is dedicated to the study of Gaussian priors for patch-based image denoising. In the last 12 years, patch priors have been widely used for image restoration. In a Bayesian framework, such priors on patches can be used for instance to estimate a clean patch from its noisy version, via classical estimators such as the conditional expectation
Delon, Julie, Houdard, Antoine
openaire   +2 more sources

Pre‐Administration of Akkermansia Muciniphila Prevents the Development of Severe Acute Graft‐Versus‐Host Disease in Systemic Organs

Advanced Science, EarlyView.
Akkermansia muciniphila, a next‐generation probiotic, alleviates acute graft‐versus‐host disease (aGvHD) following allogeneic hematopoietic stem cell transplantation (HSCT) by providing protective effects across multiple organs. Pre‐colonization with A.
Jeong‐Eun Han, Dae‐Seong Lee, Su‐Won Jeong, Ji‐Hyun Yun, Seomin Kang, Seoyoung Jang, EunAh Lee, Ju Hye Baek, Che Ok Jeon, Jin‐Woo Bae   +9 more
wiley   +1 more source

Joint Demosaicing and Denoising Based on a Variational Deep Image Prior Neural Network

Sensors, 2020
A joint demosaicing and denoising task refers to the task of simultaneously reconstructing and denoising a color image from a patterned image obtained by a monochrome image sensor with a color filter array.
Yunjin Park, Sukho Lee, Byeongseon Jeong, Jungho Yoon   +3 more
doaj   +1 more source