Results 101 to 110 of about 47,583 (209)

On the Utilization of Emoji Encoding and Data Preprocessing with a Combined CNN-LSTM Framework for Arabic Sentiment Analysis

Modelling
Social media users often express their emotions through text in posts and tweets, and these can be used for sentiment analysis, identifying text as positive or negative.
Hussam Alawneh, Ahmad Hasasneh, Mohammed Maree   +2 more
doaj   +1 more source

Destination Prediction Based on Partial Trajectory Data - Hyperparameters

, 2020
This table presents the hyperparameters retrieved after hyperparamter optimization and used to test the final models in "Destination Prediction Based on Partial Trajectory Data"
Patrick Ebel (8349384)
core   +1 more source

Random Search Plus: A more effective random search for machine learning hyperparameters optimization

, 2020
Machine learning hyperparameter optimization has always been the key to improve model performance. There are many methods of hyperparameter optimization.
Li, Bohan
core   +1 more source

EO-MTRNN: evolutionary optimization of hyperparameters for a neuro-inspired computational model of spatiotemporal learning

, 2020
For spatiotemporal learning with neural networks, hyperparameters are often set manually by a human expert. This is especially the case with multiple timescale networks that require a careful setting of the values of timescales in order to learn ...
Wieser, Erhard, Cheng, Gordon
core   +1 more source

TEGOA-CNN: An Improved Gannet Optimization Algorithm for CNN Hyperparameter Optimization in Remote Sensing Sence Classification

Remote Sensing
The evolution of remote sensing technology has led to significant improvements in high-resolution and hyperspectral image acquisition, enhancing applications like environmental monitoring and disaster assessment.
Tsu-Yang Wu, Chengyuan Yu, Haonan Li, Saru Kumari, Lip Yee Por   +4 more
doaj   +1 more source

Boosting YOLO11: Global Attention & Hyperparameter Tuning for High-Fidelity Military Aircraft Detection

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Military aircraft detection from aerial and satellite imagery is crucial for strategic surveillance and intelligence. This study evaluated the impact of the Global Attention Mechanism (GAM) and hyperparameter optimization on the performance of the YOLO11
Satyo Widijanuarto, Ema Utami
doaj   +1 more source

Hyperparameters optimization on neural networks for bond trading [PDF]

, 2018
Project Work presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Risk Analysis and ManagementArtificial Neural Networks have been recently spotlighted as de facto tools used for
Fonseca, Francisco Urbano
core  

Development of a Fully Optimized Convolutional Neural Network for Astrocytoma Classification in MRI Using Explainable Artificial Intelligence

Journal of Imaging
Astrocytoma is the most common type of brain glioma and is classified by the World Health Organization into four grades, providing prognostic insights and guiding treatment decisions.
Christos Ch. Andrianos, Spiros A. Kostopoulos, Ioannis K. Kalatzis, Dimitris Th. Glotsos, Pantelis A. Asvestas, Dionisis A. Cavouras, Emmanouil I. Athanasiadis   +6 more
doaj   +1 more source

A Hybrid Optimization Model for Transformer Fault Diagnosis Based on Gas Classification

Digital
Dissolved gas analysis (DGA) provides valuable information for transformer condition monitoring, yet accurate multi-class fault identification remains challenging due to overlapping gas patterns and the sensitivity of classifier hyperparameters.
Junju Lai, Dongpeng Weng, Feng Xian, Yuandong Xie, Yujie Chen, Qian Zhou, Chao Yuan   +6 more
doaj   +1 more source

Dynamic Priors in Bayesian Optimization for Hyperparameter Optimization

CoRR
Bayesian optimization (BO) is a widely used approach to hyperparameter optimization (HPO). However, most existing HPO methods only incorporate expert knowledge during initialization, limiting practitioners' ability to influence the optimization process as new insights emerge. This limits the applicability of BO in iterative machine learning development
Lukas Fehring, Marcel Wever, Maximilian Spliethöver, Leona Hennig, Henning Wachsmuth, Marius Lindauer   +5 more
openaire   +2 more sources