AIMC Topic: Neural Networks, Computer

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TDNN achitecture with efficient channel attention and improved residual blocks for accurate speaker recognition.

Scientific reports
In recent years, with the advancement of deep learning, Convolutional Neural Networks (CNNs) have been widely applied in speaker recognition, making CNN-based speaker embedding learning the predominant method for speaker verification. Time Delay Neur...

DASNet a dual branch multi level attention sheep counting network.

Scientific reports
Grassland sheep counting is essential for both animal husbandry and ecological balance. Accurate population statistics help optimize livestock management and sustain grassland ecosystems. However, traditional counting methods are time-consuming and c...

Optimization of biological activities of Agaricus species: an artificial intelligence-assisted approach.

Scientific reports
This study aims to determine the optimum extraction conditions that maximize the biological activities of Agaricus campestris and Agaricus bisporus species. In the study, a total of 64 extraction experiments were carried out at different temperatures...

A federated learning-based privacy-preserving image processing framework for brain tumor detection from CT scans.

Scientific reports
The detection of brain tumors is crucial in medical imaging, because accurate and early diagnosis can have a positive effect on patients. Because traditional deep learning models store all their data together, they raise questions about privacy, comp...

Advancing BCI with a transformer-based model for motor imagery classification.

Scientific reports
Brain-computer interfaces (BCIs) harness electroencephalographic signals for direct neural control of devices, offering significant benefits for individuals with motor impairments. Traditional machine learning methods for EEG-based motor imagery (MI)...

Advanced multiscale machine learning for nerve conduction velocity analysis.

Scientific reports
This paper presents an advanced machine learning (ML) framework for precise nerve conduction velocity (NCV) analysis, integrating multiscale signal processing with physiologically-constrained deep learning. Our approach addresses three fundamental li...

Explainable few-shot learning workflow for detecting invasive and exotic tree species.

Scientific reports
Deep Learning methods are notorious for relying on extensive labeled datasets to train and assess their performance. This can cause difficulties in practical situations where models should be trained for new applications for which very little data is...

Facial Emotion Recognition of 16 Distinct Emotions From Smartphone Videos: Comparative Study of Machine Learning and Human Performance.

Journal of medical Internet research
BACKGROUND: The development of automatic emotion recognition models from smartphone videos is a crucial step toward the dissemination of psychotherapeutic app interventions that encourage emotional expressions. Existing models focus mainly on the 6 b...

A novel ST-GCN model based on homologous microstate for subject-independent seizure prediction.

Scientific reports
Due to the lack of validated universal seizure markers, population-level prediction methods often exhibit limited performance. This study proposes homologous microstate dynamic attributes as a generalized, subject-independent seizure marker. Homologo...

Enhancing sarcasm detection in sentiment analysis for cyberspace safety using advanced deep learning techniques.

Scientific reports
Social media has become an integral part of daily life, with platforms like Twitter serving as popular outlets for users to share information and express grievances. While social media offers numerous benefits, it can also be misused for cyberbullyin...