AI Medical Compendium Topic:
Semantics

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Hierarchical Deep Click Feature Prediction for Fine-Grained Image Recognition.

IEEE transactions on pattern analysis and machine intelligence
The click feature of an image, defined as the user click frequency vector of the image on a predefined word vocabulary, is known to effectively reduce the semantic gap for fine-grained image recognition. Unfortunately, user click frequency data are u...

End-to-End provenance representation for the understandability and reproducibility of scientific experiments using a semantic approach.

Journal of biomedical semantics
BACKGROUND: The advancement of science and technologies play an immense role in the way scientific experiments are being conducted. Understanding how experiments are performed and how results are derived has become significantly more complex with the...

HESML: a real-time semantic measures library for the biomedical domain with a reproducible survey.

BMC bioinformatics
BACKGROUND: Ontology-based semantic similarity measures based on SNOMED-CT, MeSH, and Gene Ontology are being extensively used in many applications in biomedical text mining and genomics respectively, which has encouraged the development of semantic ...

Detection of Aerobics Action Based on Convolutional Neural Network.

Computational intelligence and neuroscience
To further improve the accuracy of aerobics action detection, a method of aerobics action detection based on improving multiscale characteristics is proposed. In this method, based on faster R-CNN and aiming at the problems existing in faster R-CNN, ...

Configurable Graph Reasoning for Visual Relationship Detection.

IEEE transactions on neural networks and learning systems
Visual commonsense knowledge has received growing attention in the reasoning of long-tailed visual relationships biased in terms of object and relation labels. Most current methods typically collect and utilize external knowledge for visual relations...

Disentangled Representation Learning for Multiple Attributes Preserving Face Deidentification.

IEEE transactions on neural networks and learning systems
Face is one of the most attractive sensitive information in visual shared data. It is an urgent task to design an effective face deidentification method to achieve a balance between facial privacy protection and data utilities when sharing data. Most...

CODER: Knowledge-infused cross-lingual medical term embedding for term normalization.

Journal of biomedical informatics
OBJECTIVE: This paper aims to propose knowledge-aware embedding, a critical tool for medical term normalization.

Multipath Cross Graph Convolution for Knowledge Representation Learning.

Computational intelligence and neuroscience
In the past, most of the entity prediction methods based on embedding lacked the training of local core relationships, resulting in a deficiency in the end-to-end training. Aiming at this problem, we propose an end-to-end knowledge graph embedding re...

NeuroCartography: Scalable Automatic Visual Summarization of Concepts in Deep Neural Networks.

IEEE transactions on visualization and computer graphics
Existing research on making sense of deep neural networks often focuses on neuron-level interpretation, which may not adequately capture the bigger picture of how concepts are collectively encoded by multiple neurons. We present Neurocartography, an ...

Cross-Modal Sentiment Sensing with Visual-Augmented Representation and Diverse Decision Fusion.

Sensors (Basel, Switzerland)
The rising use of online media has changed the social customs of the public. Users have become accustomed to sharing daily experiences and publishing personal opinions on social networks. Social data carrying emotion and attitude has provided signifi...