Convolution neural network joint with mixture of extreme learning machines for feature extraction and classification of accident images
This paper considers the accident images and develops a deep learning method for feature
extraction together with a mixture of experts for classification. For the first task, the outputs of …
extraction together with a mixture of experts for classification. For the first task, the outputs of …
Texture images classification using improved local quinary pattern and mixture of ELM-based experts
Texture images classification plays an important role in machine vision that can be used to
distinguish the surface and objects of an image from each other. Texture classification is a …
distinguish the surface and objects of an image from each other. Texture classification is a …
[HTML][HTML] Energy-aware framework for underwater mine detection system using underwater acoustic wireless sensor network
Underwater mines are considered a major threat to aquatic life, submarines, and naval
activities. Detecting and locating these mines is a challenging task, due to the nature of the …
activities. Detecting and locating these mines is a challenging task, due to the nature of the …
Improving deep learning in arrhythmia Detection: The application of modular quality and quantity controllers in data augmentation
Among the most prevalent diseases with significant fatality rates are cardiac disorders. In
recent years, the application of deep learning in diagnosing various cardiac conditions …
recent years, the application of deep learning in diagnosing various cardiac conditions …
Exploring structure–property relationships in sparse data environments using mixture-of-experts models
The mixture-of-experts (MoE) framework, which enables collaborative utilization of multiple
models specialized in distinct tasks toward a new task, is especially useful for materials …
models specialized in distinct tasks toward a new task, is especially useful for materials …
Proposing an ensemble learning model based on neural network and fuzzy system for keratoconus diagnosis based on Pentacam measurements
Purpose The present study was done to evaluate efficiency of an ensemble learning
structure for automatic keratoconus diagnosis and to categorize eyes into four different …
structure for automatic keratoconus diagnosis and to categorize eyes into four different …
SPMoE: a novel subspace-projected mixture of experts model for multi-target regression problems
In this paper, we focus on modeling multi-target regression problems with high-dimensional
feature spaces and a small number of instances that are common in many real-life problems …
feature spaces and a small number of instances that are common in many real-life problems …
A regularized root–quartic mixture of experts for complex classification problems
Mixture of experts is a neural network based ensemble learning approach consisting of
several experts and a gating network. In this paper, we introduce regularized root–quartic …
several experts and a gating network. In this paper, we introduce regularized root–quartic …
Extraction of the structural mode shapes utilizing image processing method and data fusion
Dynamic properties of structures, such as natural frequency, mode shapes, and dam**
ratios, play a decisive role in the structural behavior against dynamic loads such as …
ratios, play a decisive role in the structural behavior against dynamic loads such as …
Correlation-based pruning algorithm with weight compensation for feedforward neural networks
Optimizing neural network architectures through effective pruning techniques has become
essential to balancing model complexity and accuracy. This study introduces a novel …
essential to balancing model complexity and accuracy. This study introduces a novel …