Publicatii recente
Publicatii recente
-
DeGraRec: 3D Deformable Object Reconstruction Using Graph Neural Networks and Depth Estimation (2024)
Abstract Obtaining 3D representation of objects from scenes composed out of multiple images or frames is a task that often reacquires advanced hardware and knowledge in 3D rendering. With the […]
-
Generating random complex networks with network motifs using evolutionary algorithm-based null model (2024)
Abstract Network motifs in complex networks signify critical patterns of connections essential for deciphering system dynamics. Identifying and understanding these rare and elusive motifs is crucial for analyzing complex network […]
-
Matching Apictorial Puzzle Pieces Using Deep Learning (2024)
Abstract Finding matches between puzzle pieces is a difficult problem relevant to applications that involve restoring broken objects. The main difficulty comes from the similarity of the puzzle pieces and […]
-
Machine Learning Model Predicts Postoperative Outcomes in Chronic Rhinosinusitis With Nasal Polyps (2024)
Abstract Objective: Evaluating the possibility of predicting chronic rhinosinusitis with nasal polyps (CRSwNP) disease course using Artificial Intelligence. Methods: We prospectively included patients undergoing first endoscopic sinus surgery (ESS) for […]
-
The Impact of Data Annotations on the Performance of Object Detection Models in Icon Detection for GUI Images (2024)
Abstract Detecting icons in Graphical User Interfaces (GUIs) is essential for effective application automation. This study examines the impact of different annotation methods on the performance of object detection models for icon […]
-
A Nash equilibria decision tree for binary classification (2024)
Abstract Decision trees rank among the most popular and efficient classification methods. They are used to represent rules for recursively partitioning the data space into regions from which reliable predictions […]
-
A game theoretic decision forest for feature selection and classification (2024)
Abstract Classification and feature selection are two of the most intertwined problems in machine learning. Decision trees (DTs) are straightforward models that address these problems offering also the advantage of […]
-
Improving Unsupervised Graph-Based Skull Stripping: Enhancements and Comparative Analysis With State-Of-The-Art Methods (2024)
Abstract Brain disorders are increasingly prevalent today, making accurate brain segmentation essential for effective treatment andrecovery. This paperintroducesanenhancedunsupervisedgraph-basedbrainsegmentationmethod that employs an ellipsoid to select the nodes forming the graph. The […]
-
Teeth segmentation and carious lesions segmentation in panoramic X-ray images using CariSeg, a networks’ ensemble (2024)
Abstract Background: Dental cavities are common oral diseases that can lead to pain, discomfort, and eventually, tooth loss. Early detection and treatment of cavities can prevent these negative consequences. We […]
-
Towards an interpretable breast cancer detection and diagnosis system (2024)
Abstract According to the World Health Organization, breast cancer becomes fatal only if it spreads throughout the body. Therefore, regular screening is essential. Whilst mammography is the most frequently used […]
Proiecte recente
Evenimente