Academic Articles & Research Papers

Explainable Sentiment-Based Reputational Risk Modelling in Ugandan Megaprojects

Reputational risk reflected in digital public discourse can significantly influence stakeholder perceptions, public trust, and decision-making surrounding government megaprojects. Existing computational approaches primarily focus on sentime...

Computer vision methods and algorithms for automatic detection and classification of objects in decision support systems in agriculture

The paper examines aspects of developing and formalizing the task of applying computer vision methods and algorithms using OpenCV (implemented in Python version 3.13 notation) for automatic detection and classification of objects in decisio...

Computer Vision System for Automatic Counting of Planting Microsites Using UAV Imagery

Mechanical site preparation by mounding is often used by the forest industry to provide optimal growth conditions for tree seedlings. Prior to planting, an essential step consists in estimating the number of mounds at each planting block, w...

Melanoma Lesion Detection and Segmentation Using YOLOv4-DarkNet and Active Contour

Melanoma is the skin cancer caused by the ultraviolet radiation from the Sun and has only 15-20% of survival rate. Late diagnosis of melanoma leads to the severe malignancy of disease, and metastasis expands to the other body organs i.e. li...

Deep learning for diagnostic and clinical decision support in companion animals: a systematic review of CNN- and LSTM-based approaches.

Computer Vision Analysis of Intraoperative Video

OBJECTIVE(S): To develop and assess AI algorithms to identify operative steps in laparoscopic sleeve gastrectomy (LSG). BACKGROUND: Computer vision, a form of artificial intelligence (AI), allows for quantitative analysis of video by comput...

Artificial neural networks

Artificial neural networks now are used in many fields. They have become well established as viable, multipurpose, robust computational methodologies with solid theoretic support and with strong potential to be effective in any discipline, ...

Predicting process behaviour using deep learning

Deep learning and radiomics in precision medicine

INTRODUCTION: The radiological reading room is undergoing a paradigm shift to a symbiosis of computer science and radiology using artificial intelligence integrated with machine and deep learning with radiomics to better define tissue chara...

Deep learning in cancer diagnosis, prognosis and treatment selection

Deep learning is a subdiscipline of artificial intelligence that uses a machine learning technique called artificial neural networks to extract patterns and make predictions from large data sets. The increasing adoption of deep learning acr...

Time-series forecasting with deep learning: a survey

Numerous deep learning architectures have been developed to accommodate the diversity of time-series datasets across different domains. In this article, we survey common encoder and decoder designs used in both one-step-ahead and multi-hori...

Development of Machine Learning Models to Predict Compressed Sward Height in Walloon Pastures Based on Sentinel-1, Sentinel-2 and Meteorological Data Using Multiple Data Transformations

Accurate information about the available standing biomass on pastures is critical for the adequate management of grazing and its promotion to farmers. In this paper, machine learning models are developed to predict available biomass express...

Machine Learning in Agriculture: A Review

Machine learning has emerged with big data technologies and high-performance computing to create new opportunities for data intensive science in the multi-disciplinary agri-technologies domain. In this paper, we present a comprehensive revi...

Leveraging Cloud Technology for Personalized Multiple Sclerosis Care: A Comprehensive Data Management and Visualization Approach

This project develops a cloud-based solution for securely managing clinical data and patient-reported outcomes (PROMs) for multiple sclerosis (MS) patients. Utilizing REDCap for data collection, we incorporated clinical outcomes and PROMs f...

Artificial intelligence: Implications for the future of work

Artificial intelligence (AI) is a broad transdisciplinary field with roots in logic, statistics, cognitive psychology, decision theory, neuroscience, linguistics, cybernetics, and computer engineering. The modern field of AI began at a smal...

Fairness in multimodal machine learning applications in clinical decision support: a systematic review.

Artificial intelligence-assisted perioperative risk prediction, decision support, and supervised automation in anesthesia: A narrative review.

Artificial intelligence tools in dermatology education: A scoping review on their application, efficacy, and limitations

Introduction: Artificial Intelligence (AI) is increasingly explored for medical education, and dermatology, with its visual diagnostic focus, holds promise for AI-enhanced learning. However, evidence on its educational effectiveness remains...

Big Data for Energy Management and Energy-Efficient Buildings

European buildings are producing a massive amount of data from a wide spectrum of energy-related sources, such as smart meters’ data, sensors and other Internet of things devices, creating new research challenges. In this context, the aim o...

Expert system for managing data on the competencies of a modern manager

In the modern economy, digitalization has become one of the key components of the Russian Federation regions socio-economic development. Enterprises of various industries are faced with the need to process large amounts of data, which great...