Academic Articles & Research Papers

Visual servoing for robot control: Learning activities using RoboDKde robots: actividades de aprendizaje con RoboDK

Visual servo control is a key robotic control technique that uses visual feedback to dynamically adjust movements. This study, conducted within the AIM@VET project, evaluates the effectiveness of a RoboDK-based lesson with 25 vocational stu...

Up-to-Date Scoping Review of Object Detection Methods for Macro Marine Debris

Being able to accurately identify litter in a marine environment is crucial to cleaning up our seas and oceans. Research into object detection techniques to support this identification has been underway for over two decades. However, there ...

Turning Features Detection from Aerial Images: Model Development and Application on Florida’s Public Roadways

Advancements in computer vision are rapidly revolutionizing the way traffic agencies gather roadway geometry data, leading to significant savings in both time and money. Utilizing aerial and satellite imagery for data collection proves to b...

Machine Learning in Computer Vision

During last few years the computer applications have gone dramatic transformation from simple data processing to machine learning, thanks to the availability and accessibility of huge volume of data collected through sensors and internet. T...

Exploiting Three-Dimensional Gaze Tracking for Action Recognition During Bimanual Manipulation to Enhance Human–Robot Collaboration

Human–robot collaboration could be advanced by facilitating the intuitive, gaze-based control of robots, and enabling robots to recognize human actions, infer human intent, and plan actions that support human goals. Traditionally, gaze trac...

Building neural networks

Foundations. Motivation. Neural-Network Fundamentals. Single Neuron Computations. Network Computations. Network Simulation. Foundations Summary. Suggested Readings. Bibliography. Paradigms. The Backpropagation Network. The Counterpropagatio...

FPGA Implementations of Neural Networks

Applying Neural Networks: A Practical Guide

Techniques for building neural networks: introduction what are neural networks? how does neural computing differ from traditional programming? how are neural networks built? how do neural networks learn? what do I need to build an MLP? the ...

GPU implementation of neural networks

Survey on categorical data for neural networks

Abstract This survey investigates current techniques for representing qualitative data for use as input to neural networks. Techniques for using qualitative data in neural networks are well known. However, researchers continue to discover n...

Memristor-based neural networks

The synapse is a crucial element in biological neural networks, but a simple electronic equivalent has been absent. This complicates the development of hardware that imitates biological architectures in the nervous system. Now, the recent p...

Neural Networks: A Comprehensive Foundation

From the Publisher: This book represents the most comprehensive treatment available of neural networks from an engineering perspective. Thorough, well-organized, and completely up to date, it examines all the important aspects of this emer...

On optimization methods for deep learning

The predominant methodology in training deep learning advocates the use of stochastic gradient descent methods (SGDs). Despite its ease of implementation, SGDs are difficult to tune and parallelize. These problems make it challenging to dev...

A Comprehensive Survey on Graph Anomaly Detection With Deep Learning

Anomalies are rare observations (e.g., data records or events) that deviate significantly from the others in the sample. Over the past few decades, research on anomaly mining has received increasing interests due to the implications of thes...

Fundamentals of Deep Learning

This chapter deals with the basic understanding of the deep learning model. It starts with a view of artificial intelligence, machine learning, and deep learning. It also represents how these three concepts are related to each other. The en...

Deep Learning

A structure for online discussion within a framework for deep learning provides three strategies for dynamic online discussion; flexible peer, structured topic, and collaborative task discussion. This article examines the discussion structu...

Quantum Leap in Healthcare: A Comparative Analysis of AI/ML and Quantum Computing for Healthcare opportunities of the new era

The healthcare sector is undergoing rapid transformation driven by advances in artificial intelligence and machine learning, with quantum computing emerging as the next major breakthrough. This paper presents a comparative analysis of class...

Ethical and legal concerns in artificial intelligence applications for the diagnosis and treatment of lung cancer: a scoping review

IntroductionArtificial intelligence (AI) is increasingly integrating into the healthcare field, particularly in lung cancer care, including screening, diagnosis, treatment, and prognosis. While these applications offer promising advancement...

Machine learning in construction: From shallow to deep learning

The development of artificial intelligence technology is currently bringing about new opportunities in construction. Machine learning is a major area of interest within the field of artificial intelligence, playing a pivotal role in the pro...

Machine Learning and Deep Learning Approaches for CyberSecurity: A Review

The rapid evolution and growth of the internet through the last decades led to more concern about cyber-attacks that are continuously increasing and changing. As a result, an effective intrusion detection system was required to protect data...