AIMC Topic: Deep Learning

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Hybrid deep learning-enabled framework for enhancing security, data integrity, and operational performance in Healthcare Internet of Things (H-IoT) environments.

Scientific reports
The increasing reliance on Human-centric Internet of Things (H-IoT) systems in healthcare and smart environments has raised critical concerns regarding data integrity, real-time anomaly detection, and adaptive access control. Traditional security mec...

Multi-kernel inception-enhanced vision transformer for plant leaf disease recognition.

Scientific reports
The timely and precise identification of diseases in plants is essential for efficient disease control and safeguarding of crops. Manual identification of diseases requires expert knowledge in the field, and finding people with domain knowledge is ch...

Classification of first embryonic division stages of multiple Caenorhabditis species by deep learning.

NPJ systems biology and applications
The first embryonic division of Caenorhabditis elegans is a model for asymmetric cell division, and identifying the stages of cell division across related species could improve our understanding of the divergence of cellular events and mechanisms. Co...

Neural and behavioral reinstatement jointly reflect retrieval of narrative events.

Nature communications
When recalling past events, patterns of gaze position and neural activity resemble those observed during the original experience. We hypothesized that these two phenomena, known as gaze reinstatement and neural reactivation, are linked through a comm...

DERMA-OCTA: A Comprehensive Dataset and Preprocessing Pipeline for Dermatological OCTA Vessel Segmentation.

Scientific data
Optical coherence tomography angiography (OCTA) has emerged as a promising tool for non-invasive vascular imaging in dermatology. However, the field lacks standardized methods for processing and analyzing these complex images, as well as sufficient a...

Towards expert-level autonomous carotid ultrasonography with large-scale learning-based robotic system.

Nature communications
Carotid ultrasound requires skilled operators due to small vessel dimensions and high anatomical variability, exacerbating sonographer shortages and diagnostic inconsistencies. Prior automation attempts, including rule-based approaches with manual he...

Investigation into the Classification of Cough Sounds for Early Asthma Screening.

Current allergy and asthma reports
PURPOSE OF REVIEW: This review aims to explore an effective and scalable approach for early asthma detection using cough sounds. The main objective is to evaluate whether a multi-model deep learning fusion framework can improve diagnostic accuracy an...

A comprehensive survey of deep face verification systems adversarial attacks and defense strategies.

Scientific reports
Face Verification (FV) systems have exhibited remarkable performance in verification tasks and have consequently garnered extensive adoption across various applications, from identity duplication to authentication in mobile payments. However, the sur...

Predictive model integrating deep learning and clinical features based on ultrasound imaging data for surgical intervention in intussusception in children younger than 8 months.

BMJ open
OBJECTIVES: The objective of this study was to identify risk factors for enema reduction failure and to establish a combined model that integrates deep learning (DL) features and clinical features for predicting surgical intervention in intussuscepti...