Results 81 to 90 of about 161,243 (325)

Non‐Invasively Tracking an Arbitrary Deformable Object Through Scattering Media and Around Corners via Speckle Correlations

Advanced Science, EarlyView.
A speckle correlation centroid localization method (SCCLM) is proposed for non‐invasive tracking of an arbitrary deformable object through scattering media and around corners, requiring no prior information. Its effectiveness is demonstrated not only in tracking hidden objects beyond the memory effect region but also in following objects undergoing ...
Aiping Zhai, Wenjing Ji, Yan Wang, Xiyuan Luo, Wenjing Zhao, Dong Wang, Fei Liu   +6 more
wiley   +1 more source

On Designing a SwinIris Transformer Based Iris Recognition System

IEEE Access
In this paper, we discuss our proposed unified approach to iris recognition called the SwinIris. This approach works efficiently when combing a tuned version of the original Swin Transformer with a set of iris recognition processes.
Runqing Gao, Thirimachos Bourlai
doaj   +1 more source

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

Advanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez, Niladri Bhattacharjee, Yuxuan He, Giulio Galderisi, Brojogopal Sapui, Sara Mannaa, Ian O'Connor, Violetta Sessi, Peter Javorka, Thomas Mikolajick, Jens Trommer   +10 more
wiley   +1 more source

Security of Iris Recognition and Voice Recognition Techniques

Ibn Al-Haitham Journal for Pure and Applied Sciences, 2017
  Recently, biometric technologies are used widely due to their improved security that decreases cases of deception and theft. The biometric technologies use physical features and characters in the identification of individuals.
Ayad R. Raoof
doaj  

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

Design of an embedded iris recognition system for use with a multi-factor authentication system. [PDF]

, 2019
This paper describes in detail the design, manufacturing and testing of an embedded iris scanner for use with a multifactor authentication system.
Hess, Christopher David
core   +2 more sources

Iris Recognition Without Iris Normalization [PDF]

Journal of Computer Science, 2010
Problem statement: In any real time biometric system processing speed and recognition time are crucial parameters. Reducing processing time involves many parameters like normalization, FAR, FRR, management of eyelid and eyelash occlusions, size of signature etc. Normalization consumes substantial amount of time of the system.
openaire   +1 more source

Uncertainty‐Guided Selective Adaptation Enables Cross‐Platform Predictive Fluorescence Microscopy

Advanced Intelligent Discovery, EarlyView.
Deep learning models often fail when transferred to new microscopes. A novel framework overcomes this by selectively adapting the early layers governing low‐level image statistics, while freezing deep layers that encode morphology. This uncertainty‐guided approach enables robust, label‐free virtual staining across diverse systems, democratizing ...
Kai‐Wen K. Yang, Andrew Bai, Alexandra Bermudez, Yunqi Hong, Zoe Latham, Iris Sloan, Michael Liu, Vishrut Goyal, Cho‐Jui Hsieh, Neil Y. C. Lin   +9 more
wiley   +1 more source

Solving Data Overlapping Problem Using A Class‐Separable Extreme Learning Machine Auto‐Encoder

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The overlapping and imbalanced data in classification present key challenges. Class‐separable extreme learning machine auto‐encoding (CS‐ELM‐AE) is proposed, which is an enhancement of ELM‐AE that better handles overlapping data by clustering points from the same class together. Applying oversampling addresses imbalanced data.
Ekkarat Boonchieng, Wanchaloem Nadda
wiley   +1 more source

Shapley Additive Explanation for Local Class Differentiation: Local Explainability for Class Differentiation in Classification Models

Advanced Intelligent Systems, EarlyView.
An instance‐level, model‐agnostic explanation of class differentiation is introduced through SHAP‐LCD, linking probability shifts to feature‐wise Shapley contributions. The method operates on tabular and image data and is released in a fully reproducible implementation, offering a transparent way to examine, at each instance, why predictive models ...
Roxana M. Romero Luna, Hugo A. Ordoñez Erazo, Carlos A. Cobos Lozada   +2 more
wiley   +1 more source