AIMC Topic: Neural Networks, Computer

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AI-driven genetic algorithm-optimized lung segmentation for precision in early lung cancer diagnosis.

Scientific reports
Lung cancer remains the leading cause of cancer-related mortality worldwide, necessitating accurate and efficient diagnostic tools to improve patient outcomes. Lung segmentation plays a pivotal role in the diagnostic pipeline, directly impacting the ...

An optimized domain-specific shrimp detection architecture integrating conditional GAN and weighted ensemble learning.

Scientific reports
Deep learning primarily operates on images which contain hidden patterns that are quantified through pixel intensities. Deep learning is used to analyze the image patterns and to recognize the objects. The detection process includes the creation of l...

Monitoring and predicting cotton leaf diseases using deep learning approaches and mathematical models.

Scientific reports
Cotton, the backbone of global textile production, demands sustainable agricultural practices to ensure fiber, food, and environmental security. Cotton crop play an essential role in farming economies; however, production is sometimes affected by var...

Classifying and diagnosing Alzheimer's disease with deep learning using 6735 brain MRI images.

Scientific reports
Traditional diagnostic methods for Alzheimer's disease often suffer from low accuracy and lengthy processing times, delaying crucial interventions and patient care. Deep convolutional neural networks trained on MRI data can enhance diagnostic precisi...

Multi-scale fusion semantic enhancement network for medical image segmentation.

Scientific reports
The application of sophisticated computer vision techniques for medical image segmentation (MIS) plays a vital role in clinical diagnosis and treatment. Although Transformer-based models are effective at capturing global context, they are often ineff...

Automatic detection of orthodontically induced external root resorption based on deep convolutional neural networks using CBCT images.

Scientific reports
Orthodontically-induced external root resorption (OIERR) is among the most common risks in orthodontic treatment. Traditional OIERR diagnosis is limited by subjective judgement as well as cumbersome manual measurement. The research aims to develop an...

Modeling visual working memory using recurrent on-center off-surround neural network with distance dependent inhibition.

Scientific reports
This paper presents a computational model of visual working memory (VWM) that simulates the processing of spatially distributed objects and their features. The model emphasizes the prioritization of object-related information before feature-related p...

Optimizing the early diagnosis of neurological disorders through the application of machine learning for predictive analytics in medical imaging.

Scientific reports
Early diagnosis of Neurological Disorders (ND) such as Alzheimer's disease (AD) and Brain Tumors (BT) can be highly challenging since these diseases cause minor changes in the brain's anatomy. Magnetic Resonance Imaging (MRI) is a vital tool for diag...

A ubiquitous and interoperable deep learning model for automatic detection of pleomorphic gastroesophageal lesions.

Scientific reports
In recent years, artificial intelligence (AI) has been widely explored to enhance capsule endoscopy (CE), with the goal of improving the efficiency of the reading process. While most AI models have been developed for small bowel and colon analysis, t...

A dual encoder network with multiscale feature fusion and multiple pooling channel spatial attention for skin scar image segmentation.

Scientific reports
Skin scar is a prevalent dermatological concern that impacts both aesthetic appearance and psychological well-being, making precise delineation of scar tissue essential for clinical treatment. To address the challenge of scar image segmentation, this...