AIMC Topic: Recurrent Neural Networks

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An intelligent framework for visually impaired people through indoor object Detection-Based assistive system using YOLO with recurrent neural networks.

Scientific reports
Vision is a fundamental sense that profoundly impacts daily life and independence. For visually impaired people (VIP), the absence or impairment of this sense presents significant challenges, particularly in navigating their environment and identifyi...

A dual recurrent neural network model of human-like motion for artificial agents and its evaluation in a VR mirror game turing test.

Scientific reports
Action-oriented approaches to cognition which emphasize the constitutive role of sensorimotor patterns for perception are gaining importance for the study of cognitive processes in the human brain as well as for endowing artificial agents with cognit...

An optimized bidirectional recurrent neural network for kidney stone detection based on developed bald eagle search method in CT scan images.

Scientific reports
Kidney stone disease is a common syndrome and a recurring one, where it bears a 50% chance of being manifested again within ten years and may lead to serious complications like ureteral obstruction and unbearable pain. If timely intervention is consi...

Sequential temporal anticipation characterized by neural power modulation and in recurrent neural networks.

eLife
Relevant prospective moments arise intermittently, while most of the time is filled with irrelevant events, or noise, that constantly bombard our sensory systems. Thus, anticipating a few key moments necessitates disregarding what lies between the pr...

Recurrent Neural Networks Predict Future Peptide Aggregation for Drug Development.

Molecular pharmaceutics
Physical stability of an active pharmaceutical ingredient (API) is a key consideration in the development of a pharmaceutical drug. Solution conditions such as pH, excipient concentrations, and storage temperatures can impact the physical stability o...

An innovative multi-head attention mechanism-driven recurrent neural network model with feature representation fusion for enhanced image captioning to assist individuals with visual impairments.

Scientific reports
Developments in image captioning technologies played a crucial role in improving the quality of life for individuals with visual impairments, advancing better social inclusivity. Image captioning is the task of representing the visual content of the ...

Dual Attention-Based recurrent neural network and Two-Tier optimization algorithm for human activity recognition in individuals with disabilities.

Scientific reports
Human activity recognition (HAR) has been one of the active research areas for the past two years for its vast applications in several fields like remote monitoring, gaming, health, security and surveillance, and human-computer interaction. Activity ...

Neural dynamics of reversal learning in the prefrontal cortex and recurrent neural networks.

eLife
In probabilistic reversal learning, the choice option yielding reward with higher probability switches at a random trial. To perform optimally in this task, one has to accumulate evidence across trials to infer the probability that a reversal has occ...

A Decision Support System Based on multi-head convolutional and Recurrent Neural Networks for assisting physicians in diagnosing ADHD.

Computers in biology and medicine
BACKGROUND: Attention-Deficit Hyperactivity Disorder (ADHD) is highly prevalent among children and adolescents. Traditional diagnostic methods are subjective and time-consuming, underscoring the need for more objective diagnostic tools. Electroenceph...

Taming the chaos gently: a predictive alignment learning rule in recurrent neural networks.

Nature communications
Recurrent neural circuits often face inherent complexities in learning and generating their desired outputs, especially when they initially exhibit chaotic spontaneous activity. While the celebrated FORCE learning rule can train chaotic recurrent net...