AIMC Topic: Deep Learning

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Automated Facial Expression Recognition Framework Using Deep Learning.

Journal of healthcare engineering
Facial expression is one of the most significant elements which can tell us about the mental state of any person. A human can convey approximately 55% of information nonverbally and the remaining almost 45% through verbal communication. Automatic fac...

3D Virtual Modeling Realizations of Building Construction Scenes via Deep Learning Technique.

Computational intelligence and neuroscience
The architectural drawings of traditional building constructions generally require some design knowledge of the architectural plan to be understood. With the continuous development of the construction industry, the use of three-dimensional (3D) virtu...

Federated Deep Learning for the Diagnosis of Cerebellar Ataxia: Privacy Preservation and Auto-Crafted Feature Extractor.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Cerebellar ataxia (CA) is concerned with the incoordination of movement caused by cerebellar dysfunction. Movements of the eyes, speech, trunk, and limbs are affected. Conventional machine learning approaches utilizing centralised databases have been...

Deep learning for automatic segmentation of paraspinal muscle on computed tomography.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Muscle quantification is an essential step in sarcopenia evaluation.

Detecting the presence of supernumerary teeth during the early mixed dentition stage using deep learning algorithms: A pilot study.

International journal of paediatric dentistry
BACKGROUND: Supernumerary teeth are a common anomaly and are frequently observed in paediatric patients. To prevent or minimize complications, early diagnosis and treatment is ideal in children with supernumerary teeth.

Deep learning for caries detection: A systematic review.

Journal of dentistry
OBJECTIVES: Detecting caries lesions is challenging for dentists, and deep learning models may help practitioners to increase accuracy and reliability. We aimed to systematically review deep learning studies on caries detection.

Automatic detection of pneumonia in chest X-ray images using textural features.

Computers in biology and medicine
Fast and accurate diagnosis is critical for the triage and management of pneumonia, particularly in the current scenario of a COVID-19 pandemic, where this pathology is a major symptom of the infection. With the objective of providing tools for that ...

DeepDNAbP: A deep learning-based hybrid approach to improve the identification of deoxyribonucleic acid-binding proteins.

Computers in biology and medicine
Accurate identification of DNA-binding proteins (DBPs) is critical for both understanding protein function and drug design. DBPs also play essential roles in different kinds of biological activities such as DNA replication, repair, transcription, and...

A U-snake based deep learning network for right ventricle segmentation.

Medical physics
PURPOSE: Ventricular segmentation is of great importance for the heart condition monitoring. However, manual segmentation is time-consuming, cumbersome, and subjective. Many segmentation methods perform poorly due to the complex structure and uncerta...