Abstract Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. Machine learning describes the capacity of to learn from problem-specific training data automate process analytical model building and solve associated tasks. Deep is a concept based neural networks. For many applications, deep models outperform shallow traditional analysis approaches. In this article, we summarize fundamentals generate broader understanding methodical...

The term "generative AI" refers to computational techniques that are capable of generating seemingly new, meaningful content such as text, images, or audio from training data. widespread diffusion this technology with examples Dall-E 2, GPT-4, and Copilot is currently revolutionizing the way we work communicate each other. In article, provide a conceptualization generative AI an entity in socio-technical systems models, systems, applications. Based on that, introduce limitations current...

Across many industries, visual quality assurance has transitioned from a manual, labor-intensive, and error-prone task to fully automated precise assessment of industrial quality. This transition been made possible due advances in machine learning general, supervised particular. However, the majority approaches only allow identify pre-defined categories, such as certain error types on manufactured objects. New, unseen are unlikely be detected by models. As remedy, this work studies...

The booming adoption of Artificial Intelligence (AI) likewise poses benefits and challenges. In this paper, we particularly focus on the bright side AI its promising potential to face our society’s grand Given potential, different studies have already conducted valuable work by conceptualizing specific facets sustainability, including reviews Information Systems (IS) research or business values. Nonetheless, there is still little holistic knowledge at intersection IS, AI, sustainability....

Supervised machine learning methods for image analysis require large amounts of labelled training data to solve computer vision problems. The recent rise deep algorithms recognising content has led the emergence many ad-hoc labelling tools. With this survey, we capture and systematise commonalities as well distinctions between existing software. We perform a structured literature review compile underlying concepts features software such annotation expressiveness degree automation. structure...

The term "generative AI'' refers to computational techniques that are capable of generating seemingly new, meaningful content such as text, images, or audio from training data. widespread diffusion this technology with examples Dall-E 2, GPT-4, and Copilot is currently revolutionizing the way we work communicate each other. In article, provide a conceptualization generative AI an entity in socio-technical systems models, systems, applications. Based on that, introduce limitations current...

We propose Interpretable Generalized Additive Neural Networks (IGANN), a novel machine learning model that uses gradient boosting and tailored neural networks to obtain high predictive performance while being interpretable humans. derive an efficient training algorithm based on the theory of extreme machines, allows reducing process solving sequence regularized linear regressions. analyze theoretically, provide insights into rate change so-called shape functions, show computational...

Predicting next events in predictive process monitoring enables companies to manage and control processes at an early stage reduce their action distance. In recent years, approaches have steadily moved from classical statistical methods towards the application of deep neural network architectures, which outperform former enable analysis without explicit knowledge underlying model. While focus prior research was on long short-term memory architecture, more learning architectures offer...

Abstract Proactive analysis of patient pathways helps healthcare providers anticipate treatment-related risks, identify outcomes, and allocate resources. Machine learning (ML) can leverage a patient’s complete health history to make informed decisions about future events. However, previous work has mostly relied on so-called black-box models, which are unintelligible humans, making it difficult for clinicians apply such models. Our introduces PatWay-Net, an ML framework designed...

Abstract Strong demand for autonomous vehicles and the wide availability of 3D sensors are continuously fueling proposal novel methods object detection. In this paper, we provide a comprehensive survey recent developments from 2012–2021 in detection covering full pipeline input data, over data representation feature extraction to actual modules. We introduce fundamental concepts, focus on broad range different approaches that have emerged past decade, propose systematization provides...

Abstract In any data science and analytics project, the task of mapping a domain-specific problem to an adequate set mining methods by experts field is crucial step. However, these are not always available novices may be required perform task. While there several research efforts for automated method selection as means support, only few approaches consider particularities problems expressed in natural language novice. The study proposes design intelligent assistance system that takes...

Abstract Prescriptive Analytics Systems (PAS) represent the most mature iteration of business analytics, significantly enhancing organizational decision-making. Recently, research has gained traction, with various technological innovations, including machine learning and artificial intelligence, influencing design PAS. Although recent studies highlight these developments, rising trend focuses on broader implications, such as synergies delegation between systems users in decision-making...

Computer-Aided Design and Applications is an international journal on the applications of CAD CAM. It publishes papers in general domain plus emerging fields like bio-CAD, nano-CAD, soft-CAD, garment-CAD, PLM, PDM, data mining, internet, education, genetic algorithms engines. The aimed at all developers users technology to ptovide solutions for various stages design manufacturing. about technologies.

In recent years, with the advent of highly scalable artificial-neural-network-based text representation methods field natural language processing has seen unprecedented growth and sophistication. It become possible to distill complex linguistic information into multidimensional dense numeric vectors use distributional hypothesis. As a consequence, have been evolving at such quick pace that research community is struggling retain knowledge their interrelations. We contribute threefold this...