AIMC Topic: Deep Learning

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Is Homomorphic Encryption-Based Deep Learning Secure Enough?

Sensors (Basel, Switzerland)
As the amount of data collected and analyzed by machine learning technology increases, data that can identify individuals is also being collected in large quantities. In particular, as deep learning technology-which requires a large amount of analysi...

Novel deep learning-based solution for identification of prognostic subgroups in liver cancer (Hepatocellular carcinoma).

BMC bioinformatics
BACKGROUND: Liver cancer (Hepatocellular carcinoma; HCC) prevalence is increasing and with poor clinical outcome expected it means greater understanding of HCC aetiology is urgently required. This study explored a deep learning solution to detect bio...

Crowd density estimation using deep learning for Hajj pilgrimage video analytics.

F1000Research
BACKGROUND: This paper focuses on advances in crowd control study with an emphasis on high-density crowds, particularly Hajj crowds. Video analysis and visual surveillance have been of increasing importance in order to enhance the safety and security...

Deep Learning Technology in Pathological Image Analysis of Breast Tissue.

Journal of healthcare engineering
To explore the application value of the multilevel pyramid convolutional neural network (MPCNN) model based on convolutional neural network (CNN) in breast histopathology image analysis, in this study, based on CNN algorithm and softmax classifier (S...

Higher Education Curriculum Evaluation Method Based on Deep Learning Model.

Computational intelligence and neuroscience
Higher education plays an important role in the improvement of people's quality and the development of our country. Therefore, it is necessary to evaluate the higher education curriculum. This paper analyzes and constructs the deep network learning s...

Remaining Useful Life Estimation of Aircraft Engines Using a Joint Deep Learning Model Based on TCNN and Transformer.

Computational intelligence and neuroscience
The remaining useful life estimation is a key technology in prognostics and health management (PHM) systems for a new generation of aircraft engines. With the increase in massive monitoring data, it brings new opportunities to improve the prediction ...

Deep learning models to predict flood events in fast-flowing watersheds.

The Science of the total environment
This study aims to explore the reliability of flood warning forecasts based on deep learning models, in particular Long-Short Term Memory (LSTM) architecture. We also wish to verify the applicability of flood event predictions for a river with flood ...

Multi-class deep learning segmentation and automated measurements in periodontal sonograms of a porcine model.

Dento maxillo facial radiology
OBJECTIVES: Ultrasound emerges as a complement to cone-beam computed tomography in dentistry, but struggles with artifacts like reverberation and shadowing. This study seeks to help novice users recognize soft tissue, bone, and crown of a dental sono...

Left ventricular non-compaction cardiomyopathy automatic diagnosis using a deep learning approach.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Left ventricular non-compaction (LVNC) is an uncommon cardiomyopathy characterised by a thick and spongy left ventricle wall caused by the high presence of trabeculae (hyper-trabeculation). Recently, the percentage of the tr...

Calcium Scoring at Coronary CT Angiography Using Deep Learning.

Radiology
Background Separate noncontrast CT to quantify the coronary artery calcium (CAC) score often precedes coronary CT angiography (CTA). Quantifying CAC scores directly at CTA would eliminate the additional radiation produced at CT but remains challengin...