Results 81 to 90 of about 512,229 (281)
Advanced Electronic Materials, EarlyView.In this work, low‐resolution infrared imaging is combined with a 28 nm FeFET IMC architecture to enable compact, energy‐efficient edge inference. MLC FeFET devices are experimentally characterized, and controlled multi‐level current accumulation is validated at crossbar array level.
Alptekin Vardar +9 more
wiley +1 more source
Interocular blur suppression and monovision [PDF]
, 1994 The ability of the binocular system to suppress blur from the defocused eye is an important mechanism underlying the success of monovision correction. With a group of 60 new monovision wearers, we found that blur suppression ability varied substantially ...
M. J. Collins +3 more
core +1 more source
Evolution of Physical Intelligence Across Scales
Advanced Intelligent Discovery, EarlyView.By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu +7 more
wiley +1 more source
Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art
Advanced Intelligent Discovery, EarlyView.Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser +6 more
wiley +1 more source
A Self-adaptive Learning Method for Motion Blur Kernel Estimation of the Single Image
, 2022 Art. 168023, 11 S.The estimation of blur kernel is the first and principal steps in the deconvolution of single blurred image. The quality of image restoration highly depends on its estimation accuracy.
Hao, Xingxing +5 more
core +1 more source
Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics
Advanced Intelligent Discovery, EarlyView.Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong +5 more
wiley +1 more source
Motion Blur Kernel Estimation via Deep Learning
IEEE Transactions on Image Processing, 2018 The success of the state-of-the-art deblurring methods mainly depends on the restoration of sharp edges in a coarse-to-fine kernel estimation process. In this paper, we propose to learn a deep convolutional neural network for extracting sharp edges from blurred images.
Xiangyu Xu 0002 +3 more
openaire +3 more sources
Advanced Intelligent Discovery, EarlyView.The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu +11 more
wiley +1 more source
Blur Kernel Estimation by Using Bees Algorithm [PDF]
, 2016 Camera shake is a common source of degradation indigital images taken by an unmanned air vehicle (UAV).Usually, blur kernel is used to reduce the taken image. Blurkernel means the map of camera shake while photo is taken.Estimating an unknown blur kernel
ONAY, Murat
openaire +3 more sources
Advanced Intelligent Discovery, EarlyView.AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia +2 more
wiley +1 more source