AIMC Topic: Semantics

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DECNet: Dense embedding contrast for unsupervised semantic segmentation.

Neural networks : the official journal of the International Neural Network Society Jul 20, 2024
Unsupervised semantic segmentation is important for understanding that each pixel belongs to known categories without annotation. Recent studies have demonstrated promising outcomes by employing a vision transformer backbone pre-trained on an image-l...
Unsupervised Machine Learning Algorithms Semantics Image Processing, Computer-Assisted Humans Neural Networks, Computer
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Interpretable medical image Visual Question Answering via multi-modal relationship graph learning.

Medical image analysis Jul 20, 2024
Medical Visual Question Answering (VQA) is an important task in medical multi-modal Large Language Models (LLMs), aiming to answer clinically relevant questions regarding input medical images. This technique has the potential to improve the efficienc...
Image Interpretation, Computer-Assisted Humans Semantics Machine Learning
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Narrowing the semantic gaps in U-Net with learnable skip connections: The case of medical image segmentation.

Neural networks : the official journal of the International Neural Network Society Jul 17, 2024
Current state-of-the-art medical image segmentation techniques predominantly employ the encoder-decoder architecture. Despite its widespread use, this U-shaped framework exhibits limitations in effectively capturing multi-scale features through simpl...
Humans Image Processing, Computer-Assisted Neural Networks, Computer Semantics Algorithms Deep Learning
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CBG-Net: Cross-modality and cross-scale balance network with global semantics for multi-modal 3D object detection.

Neural networks : the official journal of the International Neural Network Society Jul 14, 2024
Multi-modal 3D object detection is instrumental in identifying and localizing objects within 3D space. It combines RGB images from cameras and point-clouds data from lidar sensors, serving as a fundamental technology for autonomous driving applicatio...
Image Processing, Computer-Assisted Semantics Algorithms Imaging, Three-Dimensional Humans Neural Networks, Computer
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Dual domain distribution disruption with semantics preservation: Unsupervised domain adaptation for medical image segmentation.

Medical image analysis Jul 14, 2024
Recent unsupervised domain adaptation (UDA) methods in medical image segmentation commonly utilize Generative Adversarial Networks (GANs) for domain translation. However, the translated images often exhibit a distribution deviation from the ideal due...
Humans Algorithms Semantics Image Processing, Computer-Assisted Unsupervised Machine Learning Brain Male
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Optimizing word embeddings for small dataset: a case study on patient portal messages from breast cancer patients.

Scientific reports Jul 12, 2024
Patient portal messages often relate to specific clinical phenomena (e.g., patients undergoing treatment for breast cancer) and, as a result, have received increasing attention in biomedical research. These messages require natural language processin...
Humans Semantics Patient Portals Breast Neoplasms Natural Language Processing Electronic Health Records Female
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An informative dual ForkNet for video anomaly detection.

Neural networks : the official journal of the International Neural Network Society Jul 11, 2024
An autoencoder for video anomaly detection task is a type of algorithm with the primary purpose of learning an "informative" representation of the normal data that can be used for identifying the abnormal data by learning to reconstruct a set of inpu...
Semantics Humans Algorithms Video Recording Neural Networks, Computer
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Mining core information by evaluating semantic importance for unpaired image captioning.

Neural networks : the official journal of the International Neural Network Society Jul 9, 2024
Recently, exciting progress has been made in the research of supervised image captioning. However, manually annotated image-annotation pair data is difficult and expensive to obtain. Therefore, unpaired image captioning becomes an emerging challenge....
Image Processing, Computer-Assisted Natural Language Processing Data Mining Semantics Neural Networks, Computer Humans Algorithms
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PLEASING: Exploring the historical and potential events for temporal knowledge graph reasoning.

Neural networks : the official journal of the International Neural Network Society Jul 6, 2024
Temporal Knowledge Graphs (TKGs) enable effective modeling of knowledge dynamics and event evolution, facilitating deeper insights and analysis into temporal information. Recently, extrapolation of TKG reasoning has attracted great significance due t...
Machine Learning Algorithms Humans Neural Networks, Computer Knowledge Time Factors Semantics
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Automatic semantic segmentation of EHG recordings by deep learning: An approach to a screening tool for use in clinical practice.

Computer methods and programs in biomedicine Jul 5, 2024
BACKGROUND AND OBJECTIVE: Preterm delivery is an important factor in the disease burden of the newborn and infants worldwide. Electrohysterography (EHG) has become a promising technique for predicting this condition, thanks to its high degree of sens...
Infant, Newborn Pregnancy Deep Learning Adult Humans Signal Processing, Computer-Assisted Semantics Electromyography Obstetric Labor, Premature Databases, Factual Female
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