AIMC Topic: Neural Networks, Computer

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DFCL: Dual-pathway fusion contrastive learning for blind single-image visible watermark removal.

Neural networks : the official journal of the International Neural Network Society
Digital image watermarking is a prevalent method for image copyright protection. As watermark embedding techniques evolve, research in copyright protection has increasingly extended into watermark removal. Recent advancements in deep learning and gen...

Uncertainty modeling for inductive knowledge graph embedding.

Neural networks : the official journal of the International Neural Network Society
In the process of refining Knowledge Graphs (KGs), new entities emerge, and old entities evolve, which usually updates their attribute information and neighborhood structures. This results in a distribution shift problem for entity features in the em...

Classification of α-thalassemia data using machine learning models.

Computer methods and programs in biomedicine
BACKGROUND: Around 7% of the global population has congenital hemoglobin disorders, with over 300,000 new cases of α-thalassemia annually. Diagnosis is costly and inaccurate in low-income regions, often relying on complete blood count (CBC) tests. Th...

An EEG-based emotion recognition method by fusing multi-frequency-spatial features under multi-frequency bands.

Journal of neuroscience methods
BACKGROUND: Recognition of emotion changes is of great significance to a person's physical and mental health. At present, EEG-based emotion recognition methods are mainly focused on time or frequency domains, but rarely on spatial information. Theref...

Artificial Intelligence-Enabled Novel Atrial Fibrillation Diagnosis System Using 3D Pulse Perception Flexible Pressure Sensor Array.

ACS sensors
Atrial fibrillation (AF) as one of the most common cardiovascular diseases has attracted great attention due to its high disability and mortality rate. Thus, a timely and effective recognition method for AF is of great importance for diagnosing and p...

Cyanobacteria hot spot detection integrating remote sensing data with convolutional and Kolmogorov-Arnold networks.

The Science of the total environment
Prompt and accurate monitoring of cyanobacterial blooms is essential for public health management and understanding aquatic ecosystem dynamics. Remote sensing, in particular satellite observations, presents a good alternative for continuous monitorin...

Estimation of Forces and Powers in Ergometer and Scull Rowing Based on Long Short-Term Memory Neural Networks.

Sensors (Basel, Switzerland)
Analyzing performance in rowing, e.g., analyzing force and power output profiles produced either on ergometer or on boat, is a priority for trainers and athletes. The current state-of-the-art methodologies for rowing performance analysis involve the ...

A hybrid CNN-Bi-LSTM model with feature fusion for accurate epilepsy seizure detection.

BMC medical informatics and decision making
BACKGROUND: The diagnosis and treatment of epilepsy continue to face numerous challenges, highlighting the urgent need for the development of rapid, accurate, and non-invasive methods for seizure detection. In recent years, advancements in the analys...

EEG Signals Classification Related to Visual Objects Using Long Short-Term Memory Network and Nonlinear Interval Type-2 Fuzzy Regression.

Brain topography
By gaining insights into how brain activity is encoded and decoded, we enhance our understanding of brain function. This study introduces a method for classifying EEG signals related to visual objects, employing a combination of an LSTM network and n...

Theoretical investigations on analysis and optimization of freeze drying of pharmaceutical powder using machine learning modeling of temperature distribution.

Scientific reports
This study investigates the application of various neural network-based models for predicting temperature distribution in freeze drying process of biopharmaceuticals. For heat-sensitive biopharmaceutical products, freeze drying is preferred to preven...