AIMC Topic: Neural Networks, Computer

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CSAP-UNet: Convolution and self-attention paralleling network for medical image segmentation with edge enhancement.

Computers in biology and medicine
Convolution operation is performed within a local window of the input image. Therefore, convolutional neural network (CNN) is skilled in obtaining local information. Meanwhile, the self-attention (SA) mechanism extracts features by calculating the co...

Improving Classification Performance in Dendritic Neuron Models through Practical Initialization Strategies.

Sensors (Basel, Switzerland)
A dendritic neuron model (DNM) is a deep neural network model with a unique dendritic tree structure and activation function. Effective initialization of its model parameters is crucial for its learning performance. This work proposes a novel initial...

Regional economic forecast using Elman neural networks with wavelet function.

PloS one
Recently, the economy in Guangdong province has ranked first in the country, maintaining a good growth momentum. The prediction of Gross Domestic Product (GDP) for Guangdong province is an important issue. Through predicting the GDP, it is possible t...

Control strategies for inverted pendulum: A comparative analysis of linear, nonlinear, and artificial intelligence approaches.

PloS one
An inverted pendulum is a challenging underactuated system characterized by nonlinear behavior. Defining an effective control strategy for such a system is challenging. This paper presents an overview of the IP control system augmented by a comparati...

Tongue feature dataset construction and real-time detection.

PloS one
BACKGROUND: Tongue diagnosis in traditional Chinese medicine (TCM) provides clinically important, objective evidence from direct observation of specific features that assist with diagnosis. However, the current interpretation of tongue features requi...

Automatic classification of acute lymphoblastic leukemia cells and lymphocyte subtypes based on a novel convolutional neural network.

Microscopy research and technique
Acute lymphoblastic leukemia (ALL) is a life-threatening disease that commonly affects children and is classified into three subtypes: L1, L2, and L3. Traditionally, ALL is diagnosed through morphological analysis, involving the examination of blood ...

DWSSA: Alleviating over-smoothness for deep Graph Neural Networks.

Neural networks : the official journal of the International Neural Network Society
Graph Neural Networks (GNNs) have demonstrated great potential in achieving outstanding performance in various graph-related tasks, e.g., graph classification and link prediction. However, most of them suffer from the following issue: shallow network...

Convolutional Neural Network-Driven Impedance Flow Cytometry for Accurate Bacterial Differentiation.

Analytical chemistry
Impedance flow cytometry (IFC) has been demonstrated to be an efficient tool for label-free bacterial investigation to obtain the electrical properties in real time. However, the accurate differentiation of different species of bacteria by IFC techno...

Integration of graph neural networks and genome-scale metabolic models for predicting gene essentiality.

NPJ systems biology and applications
Genome-scale metabolic models are powerful tools for understanding cellular physiology. Flux balance analysis (FBA), in particular, is an optimization-based approach widely employed for predicting metabolic phenotypes. In model microbes such as Esche...

A Physics-Informed Low-Shot Adversarial Learning for sEMG-Based Estimation of Muscle Force and Joint Kinematics.

IEEE journal of biomedical and health informatics
Muscle force and joint kinematics estimation from surface electromyography (sEMG) are essential for real-time biomechanical analysis of the dynamic interplay among neural muscle stimulation, muscle dynamics, and kinetics. Recent advances in deep neur...