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Semantics

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Multi-layer pseudo-supervision for histopathology tissue semantic segmentation using patch-level classification labels.

Medical image analysis
Tissue-level semantic segmentation is a vital step in computational pathology. Fully-supervised models have already achieved outstanding performance with dense pixel-level annotations. However, drawing such labels on the giga-pixel whole slide images...

A Novel Keyword Generation Model Based on Topic-Aware and Title-Guide.

Computational intelligence and neuroscience
Keywords are usually one or more words or phrases that describe the subject information of the document. The traditional automatic keywords extraction methods cannot obtain the keywords which do not appear in the document, and the semantic informatio...

Two-Level LSTM for Sentiment Analysis With Lexicon Embedding and Polar Flipping.

IEEE transactions on cybernetics
Sentiment analysis is a key component in various text mining applications. Numerous sentiment classification techniques, including conventional and deep-learning-based methods, have been proposed in the literature. In most existing methods, a high-qu...

Unsupervised Visual-Textual Correlation Learning With Fine-Grained Semantic Alignment.

IEEE transactions on cybernetics
With the rapid growth of multimedia data on the Internet, there has been a rapid rise in the demand for visual-textual cross-media retrieval between images and sentences. However, the heterogeneous property of visual and textual data brings huge chal...

TagSeq: Malicious behavior discovery using dynamic analysis.

PloS one
In recent years, studies on malware analysis have noticeably increased in the cybersecurity community. Most recent studies concentrate on malware classification and detection or malicious patterns identification, but as to malware activity, it still ...

A New Deep Model for Detecting Multiple Moving Targets in Real Traffic Scenarios: Machine Vision-Based Vehicles.

Sensors (Basel, Switzerland)
When performing multiple target detection, it is difficult to detect small and occluded targets in complex traffic scenes. To this end, an improved YOLOv4 detection method is proposed in this work. Firstly, the network structure of the original YOLOv...

Construction of Knowledge Graph English Online Homework Evaluation System Based on Multimodal Neural Network Feature Extraction.

Computational intelligence and neuroscience
This paper defines the data schema of the multimodal knowledge graph, that is, the definition of entity types and relationships between entities. The knowledge point entities are defined as three types of structures, algorithms, and related terms, sp...

Discovering Thematically Coherent Biomedical Documents Using Contextualized Bidirectional Encoder Representations from Transformers-Based Clustering.

International journal of environmental research and public health
The increasing expansion of biomedical documents has increased the number of natural language textual resources related to the current applications. Meanwhile, there has been a great interest in extracting useful information from meaningful coherent ...

A new deep learning approach based on bilateral semantic segmentation models for sustainable estuarine wetland ecosystem management.

The Science of the total environment
Nowadays, estuarial areas have been strongly affected by the construction of electrical power dams from upstream, downstream urbanization and many types of hazards along the coastal regions. It has resulted in significant changes in estuarine wetland...

A Study on Cross-Media Teaching Model for College English Classroom Based on Output-Driven Hypothetical Neural Network.

Computational intelligence and neuroscience
In the field of education, the development of educational big data has become an important strategic choice to promote the construction of the digital campus and educational reform, and educational big data has become a new driving force in the field...