AIMC Topic: Deep Learning

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Large-scale recognition of natural landmarks with deep learning based on biomimetic sonar echoes.

Bioinspiration & biomimetics
The ability to identify natural landmarks on a regional scale could contribute to the navigation skills of echolocating bats and also advance the quest for autonomy in natural environments with man-made systems. However, recognizing natural landmarks...

Blockchain-Based Deep Learning to Process IoT Data Acquisition in Cognitive Data.

BioMed research international
Remote health monitoring can help prevent disease at the earlier stages. The Internet of Things (IoT) concepts have recently advanced, enabling omnipresent monitoring. Easily accessible biomarkers for neurodegenerative disorders, namely, Alzheimer's ...

DGSLSTM: Deep Gated Stacked Long Short-Term Memory Neural Network for Traffic Flow Forecasting of Transportation Networks on Big Data Environment.

Big data
Deep learning and big data techniques have become increasingly popular in traffic flow forecasting. Deep neural networks have also been applied to traffic flow forecasting. Furthermore, it is difficult to determine whether neural networks can be used...

Comparison of sex determination using three methods applied to the greater sciatic notch of os coxae in a Thai population: Dry bone morphology, 2-dimensional photograph morphometry, and deep learning artificial neural network.

Medicine, science, and the law
The os coxa is commonly used for sex and age estimation with a high degree of accuracy. Our study aimed to compare the accuracy among three methods, which include a deep learning approach to increase the accuracy of sex prediction. A total sample of ...

Deep learning-based fully automated diagnosis of melanocytic lesions by using whole slide images.

The Journal of dermatological treatment
BACKGROUND: Erroneous diagnoses of melanocytic lesions (benign, atypical, and malignant types) result in inappropriate surgical treatment plans.

Polycystic liver: automatic segmentation using deep learning on CT is faster and as accurate compared to manual segmentation.

European radiology
OBJECTIVE: This study aimed to develop and investigate the performance of a deep learning model based on a convolutional neural network (CNN) for the automatic segmentation of polycystic livers at CT imaging.

Decision Support Systems in HF based on Deep Learning Technologies.

Current heart failure reports
PURPOSE OF REVIEW: Application of deep learning (DL) is growing in the last years, especially in the healthcare domain. This review presents the current state of DL techniques applied to electronic health record structured data, physiological signals...

Deep Learning Post-Filtering Using Multi-Head Attention and Multiresolution Feature Fusion for Image and Intra-Video Quality Enhancement.

Sensors (Basel, Switzerland)
The paper proposes a novel post-filtering method based on convolutional neural networks (CNNs) for quality enhancement of RGB/grayscale images and video sequences. The lossy images are encoded using common image codecs, such as JPEG and JPEG2000. The...

An End-to-End Deep Learning Pipeline for Football Activity Recognition Based on Wearable Acceleration Sensors.

Sensors (Basel, Switzerland)
Action statistics in sports, such as the number of sprints and jumps, along with the details of the corresponding locomotor actions, are of high interest to coaches and players, as well as medical staff. Current video-based systems have the disadvant...

HDL-IDS: A Hybrid Deep Learning Architecture for Intrusion Detection in the Internet of Vehicles.

Sensors (Basel, Switzerland)
Internet of Vehicles (IoV) is an application of the Internet of Things (IoT) network that connects smart vehicles to the internet, and vehicles with each other. With the emergence of IoV technology, customers have placed great attention on smart vehi...