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Identifying strawberry appearance quality based on unsupervised deep learning
The strawberry appearance is an essential standard for judging the quality, so it is crucial to accurately identify the strawberry appearance quality...
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Supervised and Unsupervised Deep Learning Approaches for EEG Seizure Prediction
Epilepsy affects more than 50 million people worldwide, making it one of the world’s most prevalent neurological diseases. The main symptom of...
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Unsupervised deep representation learning enables phenotype discovery for genetic association studies of brain imaging
Understanding the genetic architecture of brain structure is challenging, partly due to difficulties in designing robust, non-biased descriptors of...
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Weighted least square filter via deep unsupervised learning
The weighted least square (WLS) filter is a popular edge-preserving image smoother that is particularly useful for detail enhancing and HDR tone...
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Unsupervised deep learning for geometric feature detection and multilevel-multimodal image registration
Medical image registration is a crucial step in computer-assisted medical diagnosis, and has seen significant progress with the adoption of deep...
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Diabetic retinopathy detection using supervised and unsupervised deep learning: a review study
The severe progression of Diabetes Mellitus (DM) stands out as one of the most significant concerns for healthcare officials worldwide. Diabetic...
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GyroFlow+: Gyroscope-Guided Unsupervised Deep Homography and Optical Flow Learning
Existing homography and optical flow methods are erroneous in challenging scenes, such as fog, rain, night, and snow because the basic assumptions...
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Unsupervised deep learning of bright-field images for apoptotic cell classification
The classification of apoptotic and living cells is significant in drug screening and treating various diseases. Conventional supervised methods...
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Unsupervised deep consistency learning adaptation network for cardiac cross-modality structural segmentation
AbstractDeep neural networks have recently been succeessful in the field of medical image segmentation; however, they are typically subject to...
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Deformable registration of magnetic resonance images using unsupervised deep learning in neuro-/radiation oncology
PurposeAccurate deformable registration of magnetic resonance imaging (MRI) scans containing pathologies is challenging due to changes in tissue...
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Colorectal endoscopic image enhancement via unsupervised deep learning
Currently, various deep learning methods have been developed to address the image enhancement tasks based on paired high-quality images as...
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Image Classification Algorithm Based on Proposal Region Clustering Learning-Unsupervised Deep Learning
Although deep learning has achieved certain results in image classification, images are susceptible to factors such as lighting conditions, shooting...
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Physics constrained unsupervised deep learning for rapid, high resolution scanning coherent diffraction reconstruction
By circumventing the resolution limitations of optics, coherent diffractive imaging (CDI) and ptychography are making their way into scientific...
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An end-to-end intrusion detection system with IoT dataset using deep learning with unsupervised feature extraction
The rapid growth of the Internet of things (IoT) platform has implications on security vulnerabilities that need to be resolved. This requires an...
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A higher performance shape from focus strategy based on unsupervised deep learning for 3D shape reconstruction
Shape From Focus (SFF) is one of the most popular strategies for reconstructing object’s 3D shape, which doesn’t require any additional technology....
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Unsupervised anomaly detection for earthquake detection on Korea high-speed trains using autoencoder-based deep learning models
We propose a method for detecting earthquakes for high-speed trains based on unsupervised anomaly-detection techniques. In particular, we utilized...
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Procedure code overutilization detection from healthcare claims using unsupervised deep learning methods
BackgroundFraud, Waste, and Abuse (FWA) in medical claims have a negative impact on the quality and cost of healthcare. A major component of FWA in...
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Unsupervised abnormality detection in neonatal MRI brain scans using deep learning
Analysis of 3D medical imaging data has been a large topic of focus in the area of Machine Learning/Artificial Intelligence, though little work has...
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Challenges of deep unsupervised optical flow estimation for particle-image velocimetry data
In recent years, several algorithms have been proposed that leverage deep learning techniques within the analysis workflow of particle-image...
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An automated unsupervised deep learning–based approach for diabetic retinopathy detection
As per the International Diabetes Federation (IDF) report, 35–60% of people suffering from diabetic retinopathy (DR) have a history of diabetes. DR...
