The objective of this research is to evaluate the effects of Adam when used together with a wide and deep neural network. The dataset used was a diagnostic breast cancer dataset taken from UCI Machine Learning. Then, the dataset was fed into a conventional neural network for a benchmark test. Afterwards, the dataset was fed into the wide and deep neural network with and without Adam. It was found that there were improvements in the result of the wide and deep network with Adam. In conclusion, Adam is able to improve the performance of a wide and deep neural network
Recently, deep learning based techniques have garnered significant interest and popularity in a vari...
Deep learning using neural networks is becoming more and more popular. It is frequently used in area...
In this study we compare the performance of three evolutionary algorithms such as Genetic Algorithm ...
The objective of this research is to evaluate the effects of Adam when used together with a wide and...
Artificial Neural Network (ANN) is one of the modern computational methods proposed to solve increas...
Machine learning has been a computer sciences buzzword for years. The technology has a lot of potent...
As the performance of devices that conduct large-scale computations has been rapidly improved, vario...
Adopting the most suitable optimization algorithm (optimizer) for a Neural Network Model is among th...
Is early cancer detection using deep learning models reliable? The creation of expert systems based ...
Deep neural networks are traditionally trained using humandesigned stochastic optimization algorithm...
Convolutional Neural Networks (CNNs) are the primary driver of the explosion of computer vision. Ini...
Artificial intelligence technology has grown quickly in recent years. Convolutional neural network (...
Cancer is the second largest cause of mortality, responsible for one in every six deaths globally. C...
The effectiveness of using Artificial Neural Networks (ANNs) to substitute for slow function evaluat...
Alzheimer’s disease is one of the major challenges of population ageing, and diagnosis and predictio...
Recently, deep learning based techniques have garnered significant interest and popularity in a vari...
Deep learning using neural networks is becoming more and more popular. It is frequently used in area...
In this study we compare the performance of three evolutionary algorithms such as Genetic Algorithm ...
The objective of this research is to evaluate the effects of Adam when used together with a wide and...
Artificial Neural Network (ANN) is one of the modern computational methods proposed to solve increas...
Machine learning has been a computer sciences buzzword for years. The technology has a lot of potent...
As the performance of devices that conduct large-scale computations has been rapidly improved, vario...
Adopting the most suitable optimization algorithm (optimizer) for a Neural Network Model is among th...
Is early cancer detection using deep learning models reliable? The creation of expert systems based ...
Deep neural networks are traditionally trained using humandesigned stochastic optimization algorithm...
Convolutional Neural Networks (CNNs) are the primary driver of the explosion of computer vision. Ini...
Artificial intelligence technology has grown quickly in recent years. Convolutional neural network (...
Cancer is the second largest cause of mortality, responsible for one in every six deaths globally. C...
The effectiveness of using Artificial Neural Networks (ANNs) to substitute for slow function evaluat...
Alzheimer’s disease is one of the major challenges of population ageing, and diagnosis and predictio...
Recently, deep learning based techniques have garnered significant interest and popularity in a vari...
Deep learning using neural networks is becoming more and more popular. It is frequently used in area...
In this study we compare the performance of three evolutionary algorithms such as Genetic Algorithm ...
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