AIMC Topic: Neural Networks, Computer

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Advanced vision transformers and open-set learning for robust mosquito classification: A novel approach to entomological studies.

PLoS computational biology
Mosquito-related diseases pose a significant threat to global public health, necessitating efficient and accurate mosquito classification for effective surveillance and control. This work presents an innovative approach to mosquito classification by ...

Hybrid SEM-ANN model for predicting undergraduates' e-learning continuance intention based on perceived educational and emotional support.

PloS one
Based on the Expectation Confirmation Model (ECM), this study explores the impact of perceived educational and emotional support on university students' continuance intention to engage in e-learning. Researchers conducted a survey using structured qu...

A novel strategy for the MPPT in a photovoltaic system via sliding modes control.

PloS one
This paper proposes a robust maximum power point tracking algorithm based on a super twisting sliding modes controller. The underlying idea is solving the classical trajectory tracking control problem where the maximum power point defines the referen...

TSFF-Net: A deep fake video detection model based on two-stream feature domain fusion.

PloS one
With the advancement of deep forgery techniques, particularly propelled by generative adversarial networks (GANs), identifying deepfake faces has become increasingly challenging. Although existing forgery detection methods can identify tampering deta...

Novel approach for predicting fake news stance detection using large word embedding blending and customized CNN model.

PloS one
The proliferation of fake news is one of the major problems that causes personal and societal harm. In today's fast-paced digital age, misinformation spreads rapidly, often leaving individuals without the time to verify the authenticity of the inform...

Performance of image processing analysis and a deep convolutional neural network for the classification of oral cancer in fluorescence visualization.

International journal of oral and maxillofacial surgery
The aim of this prospective study was to determine the effectiveness of screening using image processing analysis and a deep convolutional neural network (DCNN) to classify oral cancers using non-invasive fluorescence visualization. The study include...

Similarity-based context aware continual learning for spiking neural networks.

Neural networks : the official journal of the International Neural Network Society
Biological brains have the capability to adaptively coordinate relevant neuronal populations based on the task context to learn continuously changing tasks in real-world environments. However, existing spiking neural network-based continual learning ...

Neurocontrol for fixed-length trajectories in environments with soft barriers.

Neural networks : the official journal of the International Neural Network Society
In this paper we present three neurocontrol problems where the analytic policy gradient via back-propagation through time is used to train a simulated agent to maximise a polynomial reward function in a simulated environment. If the environment inclu...

Personalized predictions of Glioblastoma infiltration: Mathematical models, Physics-Informed Neural Networks and multimodal scans.

Medical image analysis
Predicting the infiltration of Glioblastoma (GBM) from medical MRI scans is crucial for understanding tumor growth dynamics and designing personalized radiotherapy treatment plans. Mathematical models of GBM growth can complement the data in the pred...

Ensemble learning based on bi-directional gated recurrent unit and convolutional neural network with word embedding module for bioactive peptide prediction.

Food chemistry
Bioactive peptides, as small protein fragments, are essential mediators of diverse physiological activities, such as antimicrobial, anti-inflammatory, anticancer, antioxidant, and immunomodulatory functions. Despite their substantial potential in pha...