Dimitra-Christina KoutsiouUniversity of Thessaly | UTH · Department of Computer Science and Biomedical Informatics
Dimitra-Christina Koutsiou
PhD Student
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9
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Publications
Publications (9)
Effective shadow removal is pivotal in enhancing the visual quality of images in various applications, ranging from computer vision to digital photography. During the last decades physics and machine learning -based methodologies have been proposed; however, most of them have limited capacity in capturing complex shadow patterns due to restrictive...
Recently, Vision Transformers (ViTs) have emerged as a breakthrough in computer vision and image analysis. Still, their exceptional performance depends on the availability of large amounts of annotated training data and the availability of considerable computational resources. This naturally raises the risk of overfitting and limited generalization...
rain storm optimization (BSO) is a swarm-intelligence clustering-based algorithm inspired by the human brainstorming process. Electromagnetism-like mechanism for global optimization (EMO) is a physics-inspired optimization algorithm. In this study we propose a novel hybrid metaheuristic evolutionary algorithm that combines aspects from both BSO and...
Shadow removal is an important problem in computer vision, since the presence of shadows complicates core computer vision tasks, including image segmentation and object recognition. Most state-of-the-art shadow removal methods are based on complex deep learning architectures, which require training on a large amount of data. In this paper a novel a...
Βrainstorm Optimization (BSO) is a swarm-intelligence clustering-based algorithm inspired by the human brainstorming process. Electromagnetism-like Mechanism for global Optimization (EMO) is a physics-inspired optimization algorithm. In this study we propose a novel hybrid metaheuristic evolutionary algorithm that combines aspects from both BSO and...
Brain Storm optimization (BSO) is a swarm-based, metaheuristic for global optimization, which has been inspired by the collective behavior of human beings. In this work, a novel BSO-based variant, Determinative BSO (DBSO), is proposed and applied for image segmentation. The proposed algorithm implements a cluster-merging strategy, inspired by the p...
Shadow detection is useful in a variety of image
analysis applications, as it can improve scene understanding. Most
of the recent shadow detection approaches use near-infrared (NIR)
cameras and deep learning to provide enhanced segmentation of
the shadow areas in images. In this paper a novel shadow detection
method is proposed, exploiting the perc...
Staircase detection in natural images has several applications in the context of robotics and visually impaired navigation. Previous works are mainly based on handcrafted feature extraction and supervised learning using fully annotated images. In this work we address the problem of staircase detection in weakly labeled natural images, using a novel...