Results 221 to 230 of about 305,410 (292)

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

open access: yesAdvanced 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

Research on engine power-loss fault diagnosis method based on time-series data mining. [PDF]

open access: yesSci Rep
Feng L   +7 more
europepmc   +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

open access: yesAdvanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Majority‐Voting Overlapping Method for Error Correction in DNA Data Storage

open access: yesAdvanced 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

Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering

open access: yesAdvanced Intelligent Discovery, EarlyView.
Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley   +1 more source

Home - About - Disclaimer - Privacy