Academic Articles & Research Papers

Neural networks for wave forecasting

Approximation theory of the MLP model in neural networks

In this survey we discuss various approximation-theoretic problems that arise in the multilayer feedforward perceptron (MLP) model in neural networks. The MLP model is one of the more popular and practical of the many neural network models....

Tensorizing Neural Networks

Deep neural networks currently demonstrate state-of-the-art performance in several domains. At the same time, models of this class are very demanding in terms of computational resources. In particular, a large amount of memory is required b...

Forecasting wind with neural networks

Artificial Neural Networks: An Overview

Neural networks, also known as artificial neural networks (ANNs) or artificially generated neural networks (SNNs) are a subset of machine learning that provide the foundation of deep learning techniques. Their name and form are inspired by ...

Rule extraction: Using neural networks or for neural networks?

Fundamentals of neural networks: architectures, algorithms, and applications

1. Introduction. 2. Simple Neural Nets for Pattern Classification. 3. Pattern Association. 4. Neural Networks Based on Competition. 5. Adaptive Resonance Theory. 6. Backpropagation Neural Net. 7. A Sampler of Other Neural Nets. Glossary. Re...

Fundamentals of Neural Networks

The purpose of this study is to familiarise the reader with the foundations of neural networks. Artificial Neural Networks (ANNs) are algorithm-based systems that are modelled after Biological Neural Networks (BNNs). Neural networks are an ...

Artificial Neural Networks

Introduction to artificial neural networks

A neural network is a data processing system consisting of a large number of simple, highly interconnected processing elements in an architecture inspired by the structure of the cerebral cortex portion of the brain. Hence, neural networks ...

Neural Network for Pattern Recognition

As famously quoted by Margaret Heffernan: - “A great deal of creativity is about pattern recognition, and what you need to discern patterns is tons of data. Your mind collects that data by taking note of random details and anomalies easily ...

Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

We introduce a method to train Quantized Neural Networks (QNNs) --- neural networks with extremely low precision (e.g., 1-bit) weights and activations, at run-time. At train-time the quantized weights and activations are used for computing ...

An Introduction to Convolutional Neural Networks

Abstract: The field of machine learning has taken a dramatic twist in re- cent times, with the rise of the Artificial Neural Network (ANN). These biologically inspired computational models can far exceed the per- performance of previous for...

Deep Learning for Instance Retrieval: A Survey

In recent years a vast amount of visual content has been generated and shared from many fields, such as social media platforms, medical imaging, and robotics. This abundance of content creation and sharing has introduced new challenges, par...

Deep Learning and Data Labeling for Medical Applications

Federated Machine Learning

Today’s artificial intelligence still faces two major challenges. One is that, in most industries, data exists in the form of isolated islands. The other is the strengthening of data privacy and security. We propose a possible solution to t...

Capturing student interest in software engineering through gamification: a systematic literature review

Abstract ICT tools in education are widely used to support the aim of achieving learning outcomes by improving critical areas such as student engagement, participation, and motivation. In this study, we examine literature to explore how gam...

PG-MACO Optimization Method for Ship Pipeline Layout

Aimed at the problem of low efficiency of ship pipeline design, an optimization method of pipeline layout is proposed. An optimization mathematical model is established by comprehensively considering the engineering background of safety, ec...

EdgeAIGC: Model caching and resource allocation for edge artificial intelligence generated content

With the rapid development of generative artificial intelligence technology, the traditional cloud-based centralized model training and inference face significant limitations due to high transmission latency and costs, which restrict user-s...

Optimization of Process Parameters of Air Classifier Based on Particle Trajectory

Under the rapid development of the world’s powder technology, powder materials are used in a wide range of fields such as metallurgy, chemical industry and petroleum. Turbo air classifier is one of the most important mechanical equipment in...