Results 111 to 120 of about 5,472,482 (287)

Fuzzy modelling using a simplified rule base [PDF]

, 2004
Transparency and complexity are two major concerns of fuzzy rule-based systems. To improve accuracy and precision of the outputs, we need to increase the partitioning of the input space.
M. Shamim Khan, Fung, C.C., Khan, M.S., Chun Che Fung, Sebastian W. Khor, Khor, S.W.   +5 more
core  

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, Haseeb Muhammad, Junaid Younas, Gillian Lovell, Bianca Migliori, Andreas Dengel, Sheraz Ahmed   +6 more
wiley   +1 more source

Detection of hypersonic weak targets by high pulse repetition frequency radar based on multi‐hypothesis fuzzy‐matching radon transform

IET Radar, Sonar & Navigation
For the integration detection of near space hypersonic weak targets by high pulse repetition frequency (PRF) radar, a novel method named Multi‐Hypothesis Fuzzy‐Matching Radon transform (MHFM‐RT) is proposed for the near space hypersonic target detection ...
Wu Wei, Liu Dandan, Wang Guohong
doaj   +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, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source

DeepMapper: Attention‐Based AutoEncoder for System Identification in Wound Healing and Stage Prediction

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, Ksenia Zlobina, Michael Briden, Oscar Avalos, Héctor Carrión, Sebastian Osorio, Hsin‐ya Yang, Alexandra Nava, Michelle D. Bagood, Marco Rolandi, Roslyn Rivkah Isseroff, Marcella Gomez   +11 more
wiley   +1 more source

Scalarization of Type-1 Fuzzy Markov Chains

, 2010
8 páginasThis paper presents a method to transform Fuzzy Markov chains into Crisp Markov chains by means of an equivalence matrix derived from the concept of Scalar cardinality of a fuzzy set.
Juan C. Figueroa-García, Kalenatic, Dusko, Figueroa García, Juan Carlos, López, Cesar Amílcar, Dusko Kalenatic, Cesar Amilcar Lopez   +5 more
core   +1 more source

Parametric Analysis of Spiking Neurons in 16 nm Fin Field‐Effect Transistor Technology

Advanced Intelligent Discovery, EarlyView.
Energy efficient computing has driven a shift toward brain‐inspired neuromorphic hardware. This study explores the design of three distinct silicon neuron topologies implemented in 16 nm fin field‐Effect transistor technology. While the Axon‐Hillock design achieves gigahertz throughput, its functional fragility persists. The Morris–Lecar model captures
Logan Larsh, Raiyan Siddique, Sarah S. Sharif, Yaser Mike Banad   +3 more
wiley   +1 more source

Reasoning with Large A-Boxes in Fuzzy Description Logics using DL reasoners: An Experimental Evaluation [PDF]

, 2008
Cimiano P, Haase P, Ji Q, et al. Reasoning with Large A-Boxes in Fuzzy Description Logics using DL reasoners: An Experimental Evaluation. In: Proceedings of the ESWC Workshop on Advancing Reasoning on the Web: Scalability and Commonsense ...
Haase, Peter, Stoilos, Giorgos, Stamou, Giorgos, Tzouvaras, Vassilis, Mailis, Teofilos, Cimiano, Philipp ; https://orcid.org/, Ji, Qiu, Tran, Duc Thanh   +7 more
core  

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

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, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source

The stochastic stability and H∞‐fuzzy control of stochastic bifurcation of a doubly‐fed induction generator

Energy Science & Engineering
Considering the dynamic behavior of doubly‐fed induction generators (DFIGs) under the influence of random factors, this paper not only analyzes the phenomenon of stochastic instability and bifurcation of a DFIG dynamic variable in its random space when ...
Wei Chen, Qiangqiang Li, Zhanhong Wei, Kun Wang   +3 more
doaj   +1 more source