Academic Articles & Research Papers

CL-BPUWM: continuous learning with Bayesian parameter updating and weight memory

Abstract Catastrophic forgetting in neural networks is a common problem, in which neural networks lose information from previous tasks after training on new tasks. Although adopting a regularization method that preferentially retains the pa...

Fairness in Deep Learning: A Computational Perspective

Fairness in deep learning has attracted tremendous attention recently, as deep learning is increasingly being used in high-stake decision making applications that affect individual lives. We provide a review covering recent progresses to ta...

Distributed biconnectivity-preserving flocking with fast obstacle avoidance for UAV swarms

Abstract Obstacles in low-altitude environments force unmanned aerial vehicle (UAV) swarms to frequently alter their flight paths and communication links, which can easily cause network interruptions. It remains a significant challenge for ...

Deep Learning vs. Traditional Computer Vision

Deep Learning Techniques: An Overview

Exploiting Content Characteristics for Explainable Detection of Fake News

The proliferation of fake news threatens the integrity of information ecosystems, creating a pressing need for effective and interpretable detection mechanisms. Recent advances in machine learning, particularly with transformer-based models...

Credit Card Fraud Detection Using AdaBoost and Majority Voting

Credit card fraud is a serious problem in financial services. Billions of dollars are lost due to credit card fraud every year. There is a lack of research studies on analyzing real-world credit card data owing to confidentiality issues. In...

Inferring Markovian quantum master equations of few-body observables in interacting spin chains

Full information about a many-body quantum system is usually out-of-reach due to the exponential growth—with the size of the system—of the number of parameters needed to encode its state. Nonetheless, in order to understand the complex phen...

Machine learning and deep learning

Abstract Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. Machine learning describes the capacity of systems to learn from problem-specific training data to automate the process of a...

Artificial intelligence and professional roles

2017 promises to be the year that artificial intelligence (AI) moves out of film and fiction and into the workplace. While automation has become commonplace in retail and services, from the ubiquitous uptake of automatic tills to the growin...

Advanced Artificial Intelligence

Artificial intelligence is a branch of computer science and a discipline in the study of machine intelligence, that is, developing intelligent machines or intelligent systems imitating, extending and augmenting human intelligence through ar...

Privacy and Artificial Intelligence

Artificial intelligence is a rapidly developing field of research with many practical applications. Congruent to advances in technologies that enable big data, deep learning, and neural networks to train, learn, and predict, artificial inte...

Impact of AI-quantified fluid dynamics on visual outcomes over 5 years in patients with treatment-naïve nAMD from the FRB! registry

Abstract To investigate the impact of retinal fluid dynamics on visual outcomes in patients with treatment-naïve neovascular age-related macular degeneration (nAMD) treated in the real world over 5 years using approved AI-based fluid monito...

Artificial Intelligence: A Guide to Intelligent Systems

From the Publisher: Virtually all the literature on artificial intelligence is expressed in the jargon of commuter science, crowded with complex matrix algebra and differential equations. Unlike many other books on computer intelligence, t...

From AI Readiness to Human Readiness: A Human-Centered Framework for AI Adoption in SMEs

Artificial intelligence (AI) is transforming organizations across all sectors, yet many AI initiatives fail despite significant technological investments. Existing research has primarily explained AI adoption through technological, organiza...

Artificial intelligence in recommender systems

Abstract Recommender systems provide personalized service support to users by learning their previous behaviors and predicting their current preferences for particular products. Artificial intelligence (AI), particularly computational intel...

The meta-analysis of smart data international researches

Smart data is the raw material for many activities such as automation, intelligent systems, artificial intelligence and for the fourth industrial revolution. The purpose of this study is to systematically analyze all smart data related stud...

Evolving artificial intelligence

The majority of research in artificial intelligence has been devoted to modeling the symptoms of intelligent behavior as we observe them in ourselves. Investigation into the causative factors of intelligence have been passed over in order t...

Artificial intelligence in medicine

INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting ou...

Artificial Intelligence

Abstract Over the coming decades, Artificial Intelligence will profoundly impact the way we live, work, wage war, play, seek a mate, educate our young, and care for our elderly. It is likely to greatly increase our aggregate wealth, but it ...