Titlebook: Advances in Soft Computing; 23rd Mexican Interna Lourdes Martínez-Villaseñor,Gilberto Ochoa-Ruiz Conference proceedings 2025 The Editor(s)

Banister

Leveraging Pre-trained Models for Robust Federated Learning for Kidney Stone Type Recognitionand 77.2% during FRV stage, showing enhanced diagnostic accuracy and robustness against image corruption. This highlights the potential of merging pre-trained models with FL to address privacy and performance concerns in medical diagnostics, and guarantees improved patient care and enhanced trust in

接合

GIDDY

有斑点

Literatur und Untersuchungsansatz,competitive architectures. This study highlights the efficacy of leveraging lower-fidelity estimates in NAS and paves the way for further research into accelerating the design of efficient CNN architectures.

减震

Fulminate

Literatur und Untersuchungsansatz,ocal optima early. This research highlights the importance of selecting appropriate binarization strategies and suggests further exploration of chaotic maps to enhance the performance of metaheuristic algorithms in solving binary combinatorial optimization problems.

神化怪物

padding

Literatur und Untersuchungsansatz,ile Rank GA with PB-LS excels in quickly improving solutions, Rank GA with the penalty mechanism offers a broader search, capturing diverse solutions. The experimental results on various grid sizes highlight the strengths and trade-offs of each approach..This paper provides a comprehensive analysis

刚毅

https://doi.org/10.1007/978-3-8350-9497-0he P300 speller is proposed to validate it on 8 users creating a non-invasive EEG based user authentication scheme. This framework achieved a performance of 100% accuracy in user recognition for the deep neural network (DNN) classifier, highlighting its effectiveness in accurately identifying and au

冒烟