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Semantics

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Multidimensional Latent Semantic Networks for Text Humor Recognition.

Sensors (Basel, Switzerland)
Humor is a special human expression style, an important "lubricant" for daily communication for people; people can convey emotional messages that are not easily expressed through humor. At present, artificial intelligence is one of the popular resear...

Color Design Decisions for Ceramic Products Based on Quantification of Perceptual Characteristics.

Sensors (Basel, Switzerland)
The appearance characteristics of ceramic color are an important factor in determining the user's aesthetic perception of the product. Given the problem that ceramic color varies and the user's visual sensory evaluation of color is highly subjective ...

Sentiment Analysis of Animated Film Reviews Using Intelligent Machine Learning.

Computational intelligence and neuroscience
Film is an essential expression of a country's cultural soft power in terms of cross-cultural exchange. In addition, film is also the most direct and favourable means of communication. Along with the expansion and development of the Chinese film mark...

Investigating the Bilateral Connections in Generative Zero-Shot Learning.

IEEE transactions on cybernetics
Zero-shot learning (ZSL) is a pretty intriguing topic in the computer vision community since it handles novel instances and unseen categories. In a typical ZSL setting, there is a main visual space and an auxiliary semantic space. Most existing ZSL m...

, Enhancing Long-Term Consistency of Object-Oriented Semantic Maps in Robotics.

Sensors (Basel, Switzerland)
This paper proposes , a method for building object-oriented semantic maps that remain consistent in the long-term operation of mobile robots. Among the different challenges that compromise this aim, focuses on two of the more relevant ones: preventi...

Toward a standard formal semantic representation of the model card report.

BMC bioinformatics
BACKGROUND: Model card reports aim to provide informative and transparent description of machine learning models to stakeholders. This report document is of interest to the National Institutes of Health's Bridge2AI initiative to address the FAIR chal...

Semantic segmentation of human cell nucleus using deep U-Net and other versions of U-Net models.

Network (Bristol, England)
The deep learning models play an essential role in many areas, including medical image analysis. These models extract important features without human intervention. In this paper, we propose a deep convolution neural network, named as deep U-Net mode...

Semantic Analysis Technology of English Translation Based on Deep Neural Network.

Computational intelligence and neuroscience
English translation plays an important role in the development of science and technology and cultural exchanges. With the increase in translation volume, intelligent translation has become inevitable, but there is no effective solution for semantic t...

Heuristic Attention Representation Learning for Self-Supervised Pretraining.

Sensors (Basel, Switzerland)
Recently, self-supervised learning methods have been shown to be very powerful and efficient for yielding robust representation learning by maximizing the similarity across different augmented views in embedding vector space. However, the main challe...

Realization of English Instructional Resources Clusters Reconstruction System Using the Machine Learning Model.

Computational intelligence and neuroscience
Based on ML algorithm, this paper puts forward a method that can search instructional resources through keyword indexing technology, and then cluster and recombine the related results and present them centrally. In this paper, the semantic processing...