Symmetry Alignment–Feature Interaction Network for Human Ear Similarity Detection and Authentication DOI Open Access

Li Yuan,

H. Zhou,

Jiangyun Li

и другие.

Symmetry, Год журнала: 2025, Номер 17(5), С. 654 - 654

Опубликована: Апрель 26, 2025

In the context of ear-based biometric identity authentication, symmetry between left and right ears emerges as a pivotal factor, particularly when registration involves one ear authentication utilizes its contralateral counterpart. The extent to which bilateral supports consistent verification warrants significant investigation. This study addresses this challenge by proposing novel framework, Symmetry Alignment–Feature Interaction Network, designed enhance robustness. proposed network incorporates Alignment Module, leveraging differentiable geometric alignment dual-attention mechanism achieve precise feature correspondence ears, thereby mitigating robustness deficiencies conventional methods under pose variations. Additionally, Feature Network is introduced amplify nonlinear interdependencies binaural features, employing difference–product dual-path architecture discriminability through Dual-Path Similarity Fusion. Experimental validation on dataset from University Science Technology Beijing demonstrates that method achieves similarity detection accuracy 99.03% (a 9.11% improvement over baseline ResNet18) an F1 score 0.9252 in tasks. Ablation experiments further confirm efficacy reducing false positive rate 3.05%, combination with shrinking standard deviation distributions negative samples 67%. A multi-task loss function, governed dynamic weighting mechanism, effectively balances learning objectives. work establishes new paradigm for features symmetry, integrating modeling Fusion advance precision authentication.

Язык: Английский

Will Big Data and AI Redefine Indonesia’s Financial Future? DOI
Kurniawan Arif Maspul,

Nugrahani Kartika Putri

Jurnal Bisnis dan Komunikasi Digital, Год журнала: 2025, Номер 2(2), С. 21 - 21

Опубликована: Фев. 14, 2025

The rapid integration of big data and artificial intelligence (AI) is fundamentally reshaping Indonesia’s financial sector, driving unprecedented efficiency, innovation, inclusion. As Southeast Asia’s largest digital economy, Indonesia has embraced fintech solutions that leverage predictive analytics, machine learning, automation to enhance risk management, streamline transactions, expand services previously underserved populations. This transformation aligns with global trends, yet it presents distinct regulatory, infrastructural, ethical challenges. Drawing from Schumpeter’s Innovation Theory, Information Asymmetry Transaction Cost Economics, this study explores how AI redefine operations, improve decision-making, reduce market inefficiencies in the Indonesian banking ecosystem. Utilizing a qualitative phenomenological approach, research synthesizes insights industry experts, regulatory bodies, analysts assess implications data-driven strategies. Findings reveal while optimizes assessment, fraud detection, customer segmentation, hurdles, cybersecurity risks, literacy gaps remain key barriers sustainable adoption. continues its trajectory toward data-centric infrastructure, balancing technological advancement prudence will be critical shaping an inclusive resilient future. contributes ongoing discourse on intersection digitalization, economic policy, deployment emerging markets.

Язык: Английский

Процитировано

1
Symmetry Alignment–Feature Interaction Network for Human Ear Similarity Detection and Authentication DOI Open Access

Li Yuan,

H. Zhou,

Jiangyun Li

и другие.

Symmetry, Год журнала: 2025, Номер 17(5), С. 654 - 654

Опубликована: Апрель 26, 2025

In the context of ear-based biometric identity authentication, symmetry between left and right ears emerges as a pivotal factor, particularly when registration involves one ear authentication utilizes its contralateral counterpart. The extent to which bilateral supports consistent verification warrants significant investigation. This study addresses this challenge by proposing novel framework, Symmetry Alignment–Feature Interaction Network, designed enhance robustness. proposed network incorporates Alignment Module, leveraging differentiable geometric alignment dual-attention mechanism achieve precise feature correspondence ears, thereby mitigating robustness deficiencies conventional methods under pose variations. Additionally, Feature Network is introduced amplify nonlinear interdependencies binaural features, employing difference–product dual-path architecture discriminability through Dual-Path Similarity Fusion. Experimental validation on dataset from University Science Technology Beijing demonstrates that method achieves similarity detection accuracy 99.03% (a 9.11% improvement over baseline ResNet18) an F1 score 0.9252 in tasks. Ablation experiments further confirm efficacy reducing false positive rate 3.05%, combination with shrinking standard deviation distributions negative samples 67%. A multi-task loss function, governed dynamic weighting mechanism, effectively balances learning objectives. work establishes new paradigm for features symmetry, integrating modeling Fusion advance precision authentication.

Язык: Английский

Процитировано

0