AIMC Topic: Neural Networks, Computer

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Pyramid Pixel Context Adaption Network for Medical Image Classification With Supervised Contrastive Learning.

IEEE transactions on neural networks and learning systems
Spatial attention (SA) mechanism has been widely incorporated into deep neural networks (DNNs), significantly lifting the performance in computer vision tasks via long-range dependency modeling. However, it may perform poorly in medical image analysi...

Design and Implementation of Pavlovian Associative Memory Based on DNA Neurons.

IEEE transactions on neural networks and learning systems
In the field of biocomputing and neural networks, deoxyribonucleic acid (DNA) strand displacement (DSD) technology performs well in computation, programming, and information processing. In this article, the multiplication gate, addition gate, and thr...

Brain-Inspired Learning, Perception, and Cognition: A Comprehensive Review.

IEEE transactions on neural networks and learning systems
The progress of brain cognition and learning mechanisms has provided new inspiration for the next generation of artificial intelligence (AI) and provided the biological basis for the establishment of new models and methods. Brain science can effectiv...

Deep Geometric Learning With Monotonicity Constraints for Alzheimer's Disease Progression.

IEEE transactions on neural networks and learning systems
Alzheimer's disease (AD) is a devastating neurodegenerative condition that precedes progressive and irreversible dementia; thus, predicting its progression over time is vital for clinical diagnosis and treatment. For this, numerous studies have imple...

Learning an Autonomous Dynamic System to Encode Periodic Human Motion Skills.

IEEE transactions on neural networks and learning systems
Learning an autonomous dynamic system (ADS) encoding human motion rules has been shown as an effective way for human motion skills transfer. However, most existing approaches focus on goal-directed motion skills transfer, and the study on periodic mo...

RPI-GGCN: Prediction of RNA-Protein Interaction Based on Interpretability Gated Graph Convolution Neural Network and Co-Regularized Variational Autoencoders.

IEEE transactions on neural networks and learning systems
RNA-protein interactions (RPIs) play an important role in several fundamental cellular physiological processes, including cell motility, chromosome replication, transcription and translation, and signaling. Predicting RPI can guide the exploration of...

Brain tumor segmentation and detection in MRI using convolutional neural networks and VGG16.

Cancer biomarkers : section A of Disease markers
BackgroundIn this research, we explore the application of Convolutional Neural Networks (CNNs) for the development of an automated cancer detection system, particularly for MRI images. By leveraging deep learning and image processing techniques, we a...

Transforming physical fitness and exercise behaviors in adolescent health using a life log sharing model.

Frontiers in public health
INTRODUCTION: This study investigates the potential of a deep learning-based Life Log Sharing Model (LLSM) to enhance adolescent physical fitness and exercise behaviors through personalized public health interventions.

Supervised Machine Learning and Physics Machine Learning approach for prediction of peak temperature distribution in Additive Friction Stir Deposition of Aluminium Alloy.

PloS one
Additive friction stir deposition (AFSD) is a novel solid-state additive manufacturing technique that circumvents issues of porosity, cracking, and properties anisotropy that plague traditional powder bed fusion and directed energy deposition approac...