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Semantics

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Semi-Supervised Deep Learning Semantic Segmentation for 3D Volumetric Computed Tomographic Scoring of Chronic Rhinosinusitis: Clinical Correlations and Comparison with Lund-Mackay Scoring.

Tomography (Ann Arbor, Mich.)
BACKGROUND: The traditional Lund-Mackay score (TLMs) is unable to subgrade the volume of inflammatory disease. We aimed to propose an effective modification and calculated the volume-based modified LM score (VMLMs), which should correlate more strong...

Attributes learning network for generalized zero-shot learning.

Neural networks : the official journal of the International Neural Network Society
In the absence of unseen training data, zero-shot learning algorithms utilize the semantic knowledge shared by the seen and unseen classes to establish the connection between the visual space and the semantic space, so as to realize the recognition o...

Universal Adversarial Attack on Attention and the Resulting Dataset DAmageNet.

IEEE transactions on pattern analysis and machine intelligence
Adversarial attacks on deep neural networks (DNNs) have been found for several years. However, the existing adversarial attacks have high success rates only when the information of the victim DNN is well-known or could be estimated by the structure s...

Heterogeneous Graph Attention Network for Unsupervised Multiple-Target Domain Adaptation.

IEEE transactions on pattern analysis and machine intelligence
Domain adaptation, which transfers the knowledge from label-rich source domain to unlabeled target domains, is a challenging task in machine learning. The prior domain adaptation methods focus on pairwise adaptation assumption with a single source an...

Graph-Based Region and Boundary Aggregation for Biomedical Image Segmentation.

IEEE transactions on medical imaging
Segmentation is a fundamental task in biomedical image analysis. Unlike the existing region-based dense pixel classification methods or boundary-based polygon regression methods, we build a novel graph neural network (GNN) based deep learning framewo...

A Deep Learning-Based Chinese Semantic Parser for the Almond Virtual Assistant.

Sensors (Basel, Switzerland)
Almond is an extendible open-source virtual assistant designed to help people access Internet services and IoT (Internet of Things) devices. Both are referred to as skills here. Service providers can easily enable their devices for Almond by defining...

Smart Contract Vulnerability Detection Model Based on Multi-Task Learning.

Sensors (Basel, Switzerland)
The key issue in the field of smart contract security is efficient and rapid vulnerability detection in smart contracts. Most of the existing detection methods can only detect the presence of vulnerabilities in the contract and can hardly identify th...

Semantic Search for Large Scale Clinical Ontologies.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Finding concepts in large clinical ontologies can be challenging when queries use different vocabularies. A search algorithm that overcomes this problem is useful in applications such as concept normalisation and ontology matching, where concepts can...

GAN-Based Image Colorization for Self-Supervised Visual Feature Learning.

Sensors (Basel, Switzerland)
Large-scale labeled datasets are generally necessary for successfully training a deep neural network in the computer vision domain. In order to avoid the costly and tedious work of manually annotating image datasets, self-supervised learning methods ...

Learning to Reason on Tree Structures for Knowledge-Based Visual Question Answering.

Sensors (Basel, Switzerland)
Collaborative reasoning for knowledge-based visual question answering is challenging but vital and efficient in understanding the features of the images and questions. While previous methods jointly fuse all kinds of features by attention mechanism o...