AIMC Topic: Neural Networks, Computer

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Face identity coding in the deep neural network and primate brain.

Communications biology
A central challenge in face perception research is to understand how neurons encode face identities. This challenge has not been met largely due to the lack of simultaneous access to the entire face processing neural network and the lack of a compreh...

Multiple attention-based encoder-decoder networks for gas meter character recognition.

Scientific reports
Factories swiftly and precisely grasp the real-time data of the production instrumentation, which is the foundation for the development and progress of industrial intelligence in industrial production. Weather, light, angle, and other unknown circums...

Optimizing future well-being with artificial intelligence: self-organizing maps (SOMs) for the identification of islands of emotional stability.

Aging
In this article, we present a deep learning model of human psychology that can predict one's current age and future well-being. We used the model to demonstrate that one's baseline well-being is not the determining factor of future well-being, as pos...

A Novel Approach to Predict Brain Cancerous Tumor Using Transfer Learning.

Computational and mathematical methods in medicine
As the most prevalent and deadly malignancy, brain tumors have a dismal survival rate when they are at their most hazardous. Using mostly traditional medical image processing methods, segmenting and classifying brain malignant tumors is a challenging...

Dense Convolutional Neural Network for Detection of Cancer from CT Images.

BioMed research international
In this paper, we develop a detection module with strong training testing to develop a dense convolutional neural network model. The model is designed in such a way that it is trained with necessary features for optimal modelling of the cancer detect...

Construction and Research on Chinese Semantic Mapping Based on Linguistic Features and Sparse Self-Learning Neural Networks.

Computational intelligence and neuroscience
In this paper, we adopt the algorithms of linguistic feature Rong and sparse self-learning neural network to conduct an in-depth study and analysis of Chinese semantic mapping, which complements the emotion semantic representation ability of traditio...

A Neural Network Model for Digitizing Enterprise Carbon Assets Based on Multimodal Knowledge Mapping.

Computational intelligence and neuroscience
In this paper, a multimodal knowledge mapping approach is used to digitize enterprise carbon assets, and a corresponding neural network model is designed for use in the practical process. Rich textual entity labels associated with images are obtained...

Music Emotion Classification Method Based on Deep Learning and Improved Attention Mechanism.

Computational intelligence and neuroscience
Since the existing music emotion classification researches focus on the single-modal analysis of audio or lyrics, the correlation among models are neglected, which lead to partial information loss. Therefore, a music emotion classification method bas...

Knowledge Graph-Enabled Text-Based Automatic Personality Prediction.

Computational intelligence and neuroscience
How people think, feel, and behave primarily is a representation of their personality characteristics. By being conscious of the personality characteristics of individuals whom we are dealing with or deciding to deal with, one can competently amelior...

Research on Embedded Multifunctional Data Mining Technology Based on Granular Computing.

Computational intelligence and neuroscience
Due to the influence and limitations of the multisourced, heterogeneous, and unbalanced characteristics of embedded multifunctional data, the application effect of the current data mining technology is not good, and the accuracy is low. To solve the ...