AIMC Topic: Neural Networks, Computer

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A Neural Network Model of Smart Aging Combining Family Structure Change Factors.

Computational intelligence and neuroscience
In this paper, we analyze the changes in family structure and explore the changes in detail, based on which we construct a neural network model of smart aging. Based on the gender perspective, the individual growth model in the multilayer linear mode...

CA-XTree: Age Estimation of Grouped Gradient Regression Tree with Local Channel Attention.

Computational intelligence and neuroscience
Face age estimation has been widely used in video surveillance, human-computer interaction, market analysis, image processing analysis, and many fields. There are several problems that need to be solved in image-based face age estimation: (1) redunda...

Developing an Intelligent System with Deep Learning Algorithms for Sentiment Analysis of E-Commerce Product Reviews.

Computational intelligence and neuroscience
Most consumers rely on online reviews when deciding to purchase e-commerce services or products. Unfortunately, the main problem of these reviews, which is not completely tackled, is the existence of deceptive reviews. The novelty of the proposed sys...

A Cooperative Lightweight Translation Algorithm Combined with Sparse-ReLU.

Computational intelligence and neuroscience
In the field of natural language processing (NLP), machine translation algorithm based on Transformer is challenging to deploy on hardware due to a large number of parameters and low parametric sparsity of the network weights. Meanwhile, the accuracy...

Design of Assessment Judging Model for Physical Education Professional Skills Course Based on Convolutional Neural Network and Few-Shot Learning.

Computational intelligence and neuroscience
In recent years, the promotion of quality education and the development of curriculum and teaching materials reform have put forward higher goals and requirements for professional skills in physical education. However, there are still many shortcomin...

Automated Endotracheal Tube Placement Check Using Semantically Embedded Deep Neural Networks.

Academic radiology
RATIONALE AND OBJECTIVES: To develop artificial intelligence (AI) system that assists in checking endotracheal tube (ETT) placement on chest X-rays (CXRs) and evaluate whether it can move into clinical validation as a quality improvement tool.

TP-DDI: A Two-Pathway Deep Neural Network for Drug-Drug Interaction Prediction.

Interdisciplinary sciences, computational life sciences
Adverse drug-drug interactions (DDIs) can severely damage the body. Thus, it is essential to accurately predict DDIs. DDIs are complex processes in which many factors can cause interactions. Rather than merely considering one or two of the factors, w...

Robust deep learning-based semantic organ segmentation in hyperspectral images.

Medical image analysis
Semantic image segmentation is an important prerequisite for context-awareness and autonomous robotics in surgery. The state of the art has focused on conventional RGB video data acquired during minimally invasive surgery, but full-scene semantic seg...

Programming Molecular Systems To Emulate a Learning Spiking Neuron.

ACS synthetic biology
Hebbian theory seeks to explain how the neurons in the brain adapt to stimuli to enable learning. An interesting feature of Hebbian learning is that it is an unsupervised method and, as such, does not require feedback, making it suitable in contexts ...

Towards autonomous analysis of chemical exchange saturation transfer experiments using deep neural networks.

Journal of biomolecular NMR
Macromolecules often exchange between functional states on timescales that can be accessed with NMR spectroscopy and many NMR tools have been developed to characterise the kinetics and thermodynamics of the exchange processes, as well as the structur...