Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …

Artificial feedforward neural networks (ANN) have been traditionally trained by
backpropagation algorithms involving gradient descent algorithms. This is in order to …

Inverse kinematic equations allow the determination of the joint angles necessary for the
robotic manipulator to place a tool into a predefined position. Determining this equation is …

Grafik sinir ağları (GNN), yapay sinir ağı (ANN) ailesine mensup ve grafikler üzerinden bilgi
çıkarımı işlemi gerçekleştiren bir derin öğrenme yöntemidir. İlk kullanımı 2008 yılında …

Approximate Bayesian Computation (ABC) enables statistical inference in simulatorbased
models whose likelihoods are difficult to calculate but easy to simulate from. ABC constructs …

An intrusion detection system (IDS) is a system that monitors network traffic for malicious
activity and generates alerts. In anomaly-based detection, machine learning (ML) algorithms …

Multi-class pattern classification has many applications including speech recognition, and it
is not easy to extend from two-class neural networks (NNs). This paper presents a study …

In this bachelor thesis, I first introduce the machine learning methodology of text
classification with the goal to describe the functioning of neural networks. Then, I identify and …

For the data classification task back propagation (BP) is the most common used model to
trained artificial neural network (ANN). Various parameters were used to enhance the …

Gradient descent and backpropagation have enabled neural networks to achieve
remarkable results in many real-world applications. Despite ongoing success, training a …