AIMC Topic: Neural Networks, Computer

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Deep Learning-Based Artificial Neural Network-Cellular Automata Model in Constructing Landscape Gene in Shaanxi Ancient Towns under Rural Revitalization.

Computational intelligence and neuroscience
With the development of modern industrialization, the rational planning of land resources, especially rural settlements (RSs), has become an important part of rural revitalization. Optimizing the RS spatial layout and enhancing its evolution simulati...

Efficient Detection Method of Pig-Posture Behavior Based on Multiple Attention Mechanism.

Computational intelligence and neuroscience
Due to the low detection precision and poor robustness, the traditional pig-posture and behavior detection method is difficult to apply in the complex pig captivity environment. In this regard, we designed the HE-Yolo (High-effect Yolo) model, which ...

Fault Diagnosis of Wind Turbine Based on Convolution Neural Network Algorithm.

Computational intelligence and neuroscience
Relying on expert diagnosis, it solves the problem of fan failure efficiency and meets the needs of automatic inspection and intelligent operation monitoring of fans. In order to make up for the deficiency of intelligent diagnosis of bearing fault ba...

Graph Neural Network with Self-Supervised Learning for Noncoding RNA-Drug Resistance Association Prediction.

Journal of chemical information and modeling
Noncoding RNA(ncRNA) is closely related to drug resistance. Identifying the association between ncRNA and drug resistance is of great significance for drug development. Methods based on biological experiments are often time-consuming and small-scale....

LightFD: Real-Time Fault Diagnosis with Edge Intelligence for Power Transformers.

Sensors (Basel, Switzerland)
Power fault monitoring based on acoustic waves has gained a great deal of attention in industry. Existing methods for fault diagnosis typically collect sound signals on site and transmit them to a back-end server for analysis, which may fail to provi...

Depth Estimation for Integral Imaging Microscopy Using a 3D-2D CNN with a Weighted Median Filter.

Sensors (Basel, Switzerland)
This study proposes a robust depth map framework based on a convolutional neural network (CNN) to calculate disparities using multi-direction epipolar plane images (EPIs). A combination of three-dimensional (3D) and two-dimensional (2D) CNN-based dee...

Convolutional Neural Networks and Heuristic Methods for Crowd Counting: A Systematic Review.

Sensors (Basel, Switzerland)
The crowd counting task has become a pillar for crowd control as it provides information concerning the number of people in a scene. It is helpful in many scenarios such as video surveillance, public safety, and future event planning. To solve such t...

Accurate classification of white blood cells by coupling pre-trained ResNet and DenseNet with SCAM mechanism.

BMC bioinformatics
BACKGROUND: Via counting the different kinds of white blood cells (WBCs), a good quantitative description of a person's health status is obtained, thus forming the critical aspects for the early treatment of several diseases. Thereby, correct classif...

Improved SSD network for fast concealed object detection and recognition in passive terahertz security images.

Scientific reports
With the strengthening of global anti-terrorist measures, it is increasingly important to conduct security checks in public places to detect concealed objects carried by the human body. Research in recent years has shown that deep learning is helpful...