Results 151 to 160 of about 95,777 (258)

テンソルフロー（TensorFlow）

Journal of Japan Society for Fuzzy Theory and Intelligent Informatics, 2018
openaire   +2 more sources

Klasifikacija s TensorFlow

, 2018
U ovom radu prikazano je korištenje TensorFlowa i Kerasa u izradi modela za duboko učenje. Rješavali smo problem klasifikacije znamenaka i problem klasificiranja filmskih postera u žanrove. Za rješavanje problema klasifikacije korištena je TensorFlow duboka neuronska mreža te je objašnjena njena arhitektura i aktivacijske funkcije.
openaire   +1 more source

Artificial Intelligence‐Enhanced Electrocardiography for Predicting Paroxysmal Atrial Fibrillation From Sinus Rhythm: Impact of Data Integration Across Institutions and Devices

Annals of Noninvasive Electrocardiology, Volume 31, Issue 2, March 2026.
We developed CNN models using sinus rhythm ECG data from two institutions using distinct ECG systems. A fine‐tuned model trained on homogeneous datasets from cardiology departments consistently achieved high performance, whereas a model trained on heterogeneous datasets demonstrated lower performance.
Shinya Suzuki, Mari Amino, Nobumoto Moriai, Yoshifumi Sumioka, Akira Hyodo, Keiichi Satoh, Tsuneo Takayanagi, Takuya Umemoto, Yota Sekiguchi, Naomi Hirota, Atsuhiko Yagishita, Yuji Ikari, Taira Nakayama, Yoichi Ohnuki, Eiichiro Nagata, Jun Motogi, Takeshi Yamashita, Koichiro Yoshioka   +17 more
wiley   +1 more source

Automated <i>Mycobacterium tuberculosis</i> Detection in Multivariant Digitized Ziehl-Neelsen Staining Using Faster R-CNN Method. [PDF]

Int J Biomed Imaging
Rulaningtyas R, Bilhaq FG, Kusumaningrum D, Eric R, Ittaqillah SI, Trilaksana H, Widhyatmoko DB, Joseph AA.   +7 more
europepmc   +1 more source

Automated Residual Plot Assessment With the R Package autovi and the Shiny Application autovi.web

Australian &New Zealand Journal of Statistics, Volume 68, Issue 1, March 2026.
ABSTRACT Visual assessment of residual plots is a common approach for diagnosing linear models, but it relies on manual evaluation, which does not scale well and can lead to inconsistent decisions across analysts. The lineup protocol, which embeds the observed plot among null plots, can reduce subjectivity but requires even more human effort.
Weihao Li, Dianne Cook, Emi Tanaka, Susan VanderPlas, Klaus Ackermann   +4 more
wiley   +1 more source

Prodigy protein: Python package for zero-shot protein engineering using protein language models. [PDF]

BMC Bioinformatics
Massett M, Carr A.
europepmc   +1 more source

Deep learning‐enhanced 3D imaging unveils semaglutide impact on cardiac fibrosis

British Journal of Pharmacology, Volume 183, Issue 5, Page 1030-1047, March 2026.
Background and Purpose Myocardial fibrosis (MF), a hallmark of structural cardiac remodelling, drives disease progression across most forms of heart failure and plays a central role in heart failure with preserved ejection fraction (HFpEF). Despite its clinical relevance, effective treatments remain scarce.
Sheyla Barrado‐Ballestero, Sarah Torp Yttergren, Max Hahn, Marie Biviano Rosenkilde, Ditte Marie Jensen, Michael Christensen, Louise Thisted, Heidi Lindgreen Holmberg, Geoffrey Teixeira, Tor Biering‐Sørensen, Casper Gravesen Salinas, Urmas Roostalu   +11 more
wiley   +1 more source

Enhancing healthcare outcome with scalable processing and predictive analytics via cloud healthcare API. [PDF]

Front Digit Health
Salehi SS, Saadatfar H, Oyelere SS, Hussain S, Hassannataj Joloudari J, Taheri Ledari M, Arslan E, Barzegar B.   +7 more
europepmc   +1 more source

Generating Stable and Metastable Critical Points in Uncertain Systems via Flow‐Based Models

Expert Systems, Volume 43, Issue 3, March 2026.
ABSTRACT This work proposes the use of conditional flow‐based generative models to learn an approximation of the distribution of the critical points of a cost function. This approximation is used to incrementally identify all critical points, in the feasible domain of said function, by iteratively alternating the sampling of the distribution and the ...
Callum Wilson, Massimiliano Vasile
wiley   +1 more source

A Performance Study of Deep Neural Network Representations of Interpretable ML on Edge Devices with AI Accelerators. [PDF]

Sensors (Basel)
Schauer J, Goodarzi P, Morsch J, Schütze A.   +3 more
europepmc   +1 more source