相关论文: A Semantic-driven Approach for Maintenance Digital…
Retrieving all semantically relevant products from the product catalog is an important problem in E-commerce. Compared to web documents, product catalogs are more structured and sparse due to multi-instance fields that encode heterogeneous…
In the field of machine learning, data understanding is the practice of getting initial insights in unknown datasets. Such knowledge-intensive tasks require a lot of documentation, which is necessary for data scientists to grasp the meaning…
Nowadays, software artifacts are ubiquitous in our lives being an essential part of home appliances, cars, cell phones, and even in more critical activities like aeronautics and health sciences. In this context software failures may produce…
Domain experts are increasingly employing machine learning to solve their domain-specific problems. This article presents six key challenges that a domain expert faces in transforming their problem into a computational workflow, and then…
This chapter describes a semantic dialogue system for radiologists in a comprehensive case study within the large-scale MEDICO project. MEDICO addresses the need for advanced semantic technologies in the search for medical image and patient…
Semantic communication, an intelligent communication paradigm that aims to transmit useful information in the semantic domain, is facilitated by deep learning techniques. Robust semantic features can be learned and transmitted in an analog…
The aim of the work is to present an alternative approach to recording and evaluating student performance that enables sustainable performance recording with the possibility of integrating practical components in particular. The intended…
Drug development is becoming more and more complex and resource-intensive. To reduce the costs and the time-to-market, the pharmaceutical industry employs cutting-edge automation solutions. Supportive robotics technologies, such as…
Semantic segmentation has been widely investigated in the community, in which the state of the art techniques are based on supervised models. Those models have reported unprecedented performance at the cost of requiring a large set of high…
The paper presents a review of modern methods in the registration, processing, and analysis of dynamic processes in liquids, gases, plasmas, multiphase media, which are realized in researches and technology. The review author observes both…
The great behavioral heterogeneity observed between individuals with the same psychiatric disorder and even within one individual over time complicates both clinical practice and biomedical research. However, modern technologies are an…
Facial stylization aims to transform facial images into appealing, high-quality stylized portraits, with the critical challenge of accurately learning the target style while maintaining content consistency with the original image. Although…
Dementia care requires healthcare professionals to balance a patient's medical needs with a deep understanding of their personal needs, preferences, and emotional cues. However, current digital tools prioritise quantitative metrics over…
Linked Open Datasets about scholarly publications enable the development and integration of sophisticated end-user services; however, richer datasets are still needed. The first goal of this Challenge was to investigate novel approaches to…
The efficiency and service quality in a medical environment can be improved by using electronic documents (or e-docs) and digital signatures to speed up both doctors' activity and to provide in the same time easy retrieval and use of needed…
Systematic application of software metric techniques can lead to significant improvements of the quality of a final software product. However, there is still the evident lack of wider utilization of software metrics techniques and tools due…
Simulating physical systems is a core component of scientific computing, encompassing a wide range of physical domains and applications. Recently, there has been a surge in data-driven methods to complement traditional numerical simulations…
The massive amount of current data has led to many different forms of data analysis processes that aim to explore this data to uncover valuable insights. Methodologies to guide the development of big data science projects, including…
Analysing the development process for an ERP solution, in our case SAP, is one of the most critical processes in implementing standard software packages. Modelling of the proposed system can facilitate the development of enterprise systems…
Designers have ample opportunities to impact the healthcare domain. However, hospitals are often closed ecosystems that pose challenges in engaging clinical stakeholders, developing domain knowledge, and accessing relevant systems and data.…