Paper-Conference

Learning Gaze-aware Compositional GAN from Limited Annotations
Gaze-annotated facial data is crucial for training deep neural networks (DNNs) for gaze estimation. However, obtaining these data is …
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Multi-Level XAI-Driven MLOps Pipeline for the Adjustment of Fruit and Vegetable Classifiers
In this paper, we present a machine learning operations (MLOps) pipeline that exploits explainable artificial intelligence (XAI) to …
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Predicting Lung Infection Severity in Chest X-Ray Images Through Multi-score Assessment
Respiratory illnesses, such as COVID-19, pose a significant health challenge. The prompt and precise identification of pulmonary …
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Revolutionizing Skin Cancer Diagnosis: Unleashing AI Precision Through Deep Learning
Accurate detection methods are desperately needed, as skin cancer concerns around the world continue to rise. Conventional methods, …
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Self-supervised Vision Transformers for image-to-image labeling: a BiaPy solution to the LightMyCells Challenge
Fluorescence microscopy plays a crucial role in cellular analysis but is often hindered by phototoxicity and limited spectral channels. …
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Unsupervised data labeling and incremental cross-domain training for enhanced hybrid eye gaze estimation
This paper aims to advance the fields of unsupervised data labeling and incremental cross-domain training techniques. We apply these …
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Unsupervised data labeling and incremental cross-domain training for enhanced hybrid eye gaze estimation
Scalable Semi-Supervised Learning through Combined Anchor-based Graph and Flexible Manifold Embedding
This paper focuses on graph-based semi-supervised learning, specifically for large-scale graphs used in inductive multi-class …
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Semi-supervised Classification through Data and Label Graph Fusion
This study introduces a groundbreaking structure for semi-supervised learning based on graphs. Our technique provides an …
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Automatic Quantification of Lung Infection Severity in Chest X-ray Images
A large number of well-maintained datasets are needed for the diagnosis and assessment of the severity of the new disease (COVID-19) …
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A Comprehensive Deep Semi-supervised Graph Learning Approach Incorporating Node Re-weighting and Manifold Regularization
Deep Graph Neural Networks (GNN) have gained increasing prominence across various fields and applications in recent years. In …
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