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Toward fair graph neural networks via real counterfactual samples
Graph neural networks (GNNs) have become pivotal in various critical decision-making scenarios due to their exceptional performance. However,...
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Psychosocial factors that favor citizen participation in the generation of scientific knowledge
BackgroundCitizen participation in the generation of scientific knowledge is one of the major challenges facing science and technology systems. This...
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MGA-Net: multiscale global feature aggregation network for arteriovenous classification
Subtle retinal vascular changes and abnormalities can serve as crucial biomarkers for numerous systemic diseases. The classification of retinal...
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Extra-abdominal trocar and instrument detection for enhanced surgical workflow understanding
PurposeVideo-based intra-abdominal instrument tracking for laparoscopic surgeries is a common research area. However, the tracking can only be done...
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Aspect-based drug review classification through a hybrid model with ant colony optimization using deep learning
The task of aspect-level sentiment analysis is intricately designed to determine the sentiment polarity directed towards a specific target within a...
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Cooperative coati optimization algorithm with transfer functions for feature selection and knapsack problems
Coatis optimization algorithm (COA) has recently emerged as an innovative meta-heuristic algorithm (MA) for global optimization, garnering...
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Heterogeneous Semantic Transfer for Multi-label Recognition with Partial Labels
Multi-label image recognition with partial labels (MLR-PL), in which some labels are known while others are unknown for each image, may greatly...
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Text summarization based on semantic graphs: an abstract meaning representation graph-to-text deep learning approach
Nowadays, due to the constantly growing amount of textual information, automatic text summarization constitutes an important research area in natural...
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Exploring the dynamics of ICT and globalization on human development in India: asymmetric analysis and policy implications
The present study examines the asymmetrical relationship among globalization (GLB), information communication and technology (ICT), and human...
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A position-enhanced sequential feature encoding model for lung infections and lymphoma classification on CT images
PurposeDifferentiating pulmonary lymphoma from lung infections using CT images is challenging. Existing deep neural network-based lung CT...
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Edge highlighting with depth-dependent opacity gradation of laser-scanned point clouds improves the accuracy of perceived depth in transparent multi-view 3D visualizations
There is an activity called "digital archiving" in which cultural property is digitized for preservation and utilization, and transparent...
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Procedure-Aware Action Quality Assessment: Datasets and Performance Evaluation
In this paper, we investigate the problem of procedure-aware action quality assessment, which analyzes the action quality by delving into the...
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Application of neural networks to predict indoor air temperature in a building with artificial ventilation: impact of early stop**
Indoor air temperature prediction can facilitate energy-saving actions without compromising the indoor thermal comfort of occupants. The aim of this...
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Needle tracking in low-resolution ultrasound volumes using deep learning
PurposeClinical needle insertion into tissue, commonly assisted by 2D ultrasound imaging for real-time navigation, faces the challenge of precise...
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ASRE-KG&RS: knowledge graph and recommender system for adaptive smart radio environment
With the rapid advancement of wireless communication technologies, efficient utilization of the spectrum has become more complex and competitive....
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Analyzing processing time and load factor: 5-node mix network with ElGamal encryption and XOR shuffling
To provide anonymous communication, this paper proposes the implementation of a 5-node mix network using ElGamal encryption and XOR Shuffling. An...
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Detection of pulmonary nodules in chest radiographs: novel cost function for effective network training with purely synthesized datasets
PurposeMany large radiographic datasets of lung nodules are available, but the small and hard-to-detect nodules are rarely validated by computed...
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VLSI realization of hybrid fast fourier transform using reconfigurable booth multiplier
A discrete fourier transform (DFT) of a series of samples may be quickly and efficiently computed with the use of a mathematical procedure known as...
