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A learning artificial visual system for motion direction detection
Research on the visual system and its development is not only crucial for understanding how we see and interpret the environment from basic visual...
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An interpretable Bayesian deep learning-based approach for sustainable clean energy
Sustainable Development Goal 7 is dedicated to ensuring access to clean and affordable energy that can be utilized in various applications. Solar...
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Late sensor fusion approach with a designed multi-segmentation network
Sensors have different perceptive abilities against environment. Sensor fusion plays a crucial role at achieving better perception by accumulating...
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A study of progressive data flow knowledge tracing based on reconstructed attention mechanism
Knowledge tracing (KT) is an essential task in intellectual education, which measures learners’ ability to learn new knowledge by collecting...
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Cultural heritage digital twin: modeling and representing the visual narrative in Leonardo Da Vinci’s Mona Lisa
In this paper, Artificial Intelligence/Knowledge Representation methods are used for the digital modeling of cultural heritage elements. Accordingly,...
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AutYOLO-ATT: an attention-based YOLOv8 algorithm for early autism diagnosis through facial expression recognition
Autism Spectrum Disorder (ASD) is a developmental condition resulting from abnormalities in brain structure and function, which can manifest as...
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Neuro-symbolic artificial intelligence: a survey
The goal of the growing discipline of neuro-symbolic artificial intelligence (AI) is to develop AI systems with more human-like reasoning...
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BIDGCN: boundary-informed dynamic graph convolutional network for adaptive spline fitting of scattered data
Surface reconstruction from scattered point clouds is the process of generating surfaces from unstructured data configurations retrieved using an...
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Pose-aware video action segmentation
Action segmentation is an emerging task in video understanding, particularly for untrimmed videos containing multiple actions. However, existing...
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STOD: toward semi-supervised tiny object detection
Semi-supervised object detection aims to enhance object detectors by utilizing a large number of unlabeled images, which has gained increasing...
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PoLYTC: a novel BERT-based classifier to detect political leaning of YouTube videos based on their titles
Over two-thirds of the U.S. population uses YouTube, and a quarter of U.S. adults regularly receive their news from it. Despite the massive political...
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DSANet: dilated spatial attention network for the detection of text, non-text and touching components in unconstrained handwritten documents
Handwritten documents generated in our day-to-day office work, class room and other sectors of society carry vital information. Automatic processing...
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An integrated approach for prediction of magnitude using deep learning techniques
Timely estimation of earthquake magnitude plays a crucial role in the early warning systems for earthquakes. Despite the inherent danger associated...
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Artificial neural network evaluation of concrete performance exposed to elevated temperature with destructive–non-destructive tests
In this study, it is aimed to predict the performance of concretes obtained by using supplementary cementitious materials (SCM) before and after high...
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Enhancing omics analyses of bacterial protein secretion via non-classical pathways
Understanding the intricate pathways of protein secretion in bacteria is crucial for advancing research on bacterial diseases and their potential...
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Deep learning segmentation models for estimating the health status of induction motor bearing
The demand for accurate health status assessment of bearings in rotating electrical machines is rising. However, traditional fault diagnosis methods...
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Integrating fuzzy metrics and negation operator in FCM algorithm via genetic algorithm for MRI image segmentation
In this study, we redefine FCM algorithm by integrating fuzzy set theory, fuzzy metrics, and Sugeno negation principles. This innovative approach...
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Subspace-guided GAN for realistic single-image dehazing scenarios
Single-image haze removal is an essential preprocessing phase in many object detection and segmentation approaches. Recently, end-to-end deep...
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Exploring how a generative AI interprets music
We aim to investigate how closely neural networks (NNs) mimic human thinking. As a step in this direction, we study the behavior of artificial...
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Parameter-efficient fine-tuning of pre-trained code models for just-in-time defect prediction
Software engineering workflows use version control systems to track changes and handle merge cases from multiple contributors. This has introduced...
