Results 81 to 90 of about 983,800 (290)

Effect of hyperparameter tuning of machine learning algorithms on the modeling quality of the distribution of three mosquito species in Morocco

Journal of Intelligent Systems
The widespread use of machine learning algorithms in dataset modeling requires a thorough understanding of the various tools likely to improve the modeling quality.
Douider Meriem, Amrani Ibrahim, Abik Mounia   +2 more
doaj   +1 more source

Meta-learning approach for variational autoencoder hyperparameter tuning [PDF]

Journal of Universal Computer Science
Synthetic data generation is a promising alternative to traditional data anonymization, with Variational Autoencoders (VAEs) excelling at generating high-quality synthetic tabular datasets.
Michele Berti, Matheus Camilo da Silva, Sebastiano Saccani, Sylvio Barbon Junior   +3 more
doaj   +3 more sources

Optimized tuberculosis classification system for chest X‐ray images: Fusing hyperparameter tuning with transfer learning approaches

Engineering Reports
Advanced diagnostic methods are necessary for the prompt and reliable identification of tuberculosis (TB), which continues to be a worldwide health problem.
R. Wajgi, G. Yenurkar, V. Nyangaresi, Badal Wanjari, Sanjana Verma, Arya Deshmukh, Somesh Mallewar   +6 more
semanticscholar   +1 more source

Descriptors to Dynamics: A Materials and Device Perspective on in‐Materio Physical Reservoir Computing for Neuromorphic Edge Intelligence

Advanced Materials, EarlyView.
Intrinsic material dynamics are harnessed as computational resources for neuromorphic in‐materio physical reservoir computing. Defects, ionic motion, interfaces, percolation, geometry, and biasing shape transient states that provide fading memory, nonlinearity, and high‐dimensional projection for simple readout. A descriptor‐to‐dynamics framework links
Kshitij RB Singh, Alif Syafiq Kamarol Zaman, Muzhen Xu, Yuki Usami, Saptarshi Das, Hirofumi Tanaka   +5 more
wiley   +1 more source

Systematic Literature Review: Optimasi Model Klasifikasi pada Imbalanced Data Menggunakan SMOTE, Hyperparameter Tuning, dan Ensemble Learning

Jurnal Teknologi dan Sistem Informasi
Imbalanced Data merupakan salah satu permasalahan utama dalam pengembangan model klasifikasi karena menyebabkan model cenderung mempelajari kelas mayoritas sehingga kemampuan mendeteksi kelas minoritas menjadi menurun.
Muhammad Alfin Ghozali, Agus Bahtiar
doaj   +1 more source

Automatic hyperparameter tuning of topology optimization algorithms using surrogate optimization

Structural And Multidisciplinary Optimization
This paper presents a new approach that automates the tuning process in topology optimization of parameters that are traditionally defined by the user. The new method draws inspiration from hyperparameter optimization in machine learning.
D. Ha, Josephine V. Carstensen
semanticscholar   +1 more source

Wavelength‐Multiplexed 2D Beam Steering via a Passive Diffractive Network

Advanced Optical Materials, EarlyView.
Illustration of a wavelength‐multiplexed diffractive beam steering system, which is composed of K cascaded diffractive layers, each containing phase‐modulating elements that are jointly optimized using deep learning–based optimization. When illuminated with a set of wavelengths {λ1,λ2,…,λNw}$\{ {{{\lambda }_1},{{\lambda }_2},\ldots ,{{\lambda }_{{{N}_w}
Che‐Yung Shen, Yuhang Li, Çağatay Işıl, Tianyi Gan, Mona Jarrahi, Aydogan Ozcan   +5 more
wiley   +1 more source

Metaheuristics in automated machine learning: Strategies for optimization

Intelligent Systems with Applications
The present work explores the application of Automated Machine Learning techniques, particularly on the optimization of Artificial Neural Networks through hyperparameter tuning.
Francesco Zito, El-Ghazali Talbi, Claudia Cavallaro, Vincenzo Cutello, Mario Pavone   +4 more
doaj   +1 more source

Improving the Robustness of Visual Teach‐and‐Repeat Navigation Using Drift Error Correction and Event‐Based Vision for Low‐Light Environments

Advanced Robotics Research, EarlyView.
Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley   +1 more source

Evaluating CNN Architectures and Hyperparameter Tuning for Enhanced Lung Cancer Detection Using Transfer Learning

Journal of Electrical and Computer Engineering
Accurate lung cancer detection is vital for timely diagnosis and treatment. This study evaluates the performance of six convolutional neural network (CNN) architectures, ResNet‐50, VGG‐16, ResNet‐101, VGG‐19, DenseNet‐201, and EfficientNet‐B4, using the ...
Mohd Munazzer Ansari, Shailendra Kumar, U. Tariq, Md Belal Bin Heyat, Faijan Akhtar, Mohd Ammar Bin Hayat, Eram Sayeed, Saba Parveen, Dustin Pomary   +8 more
semanticscholar   +1 more source