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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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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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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 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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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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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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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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Dual-Fisheye Image Stitching via Unsupervised Deep Learning
Constructing panoramic images from a dual-fisheye lens has been increasingly used along with the recent booming of new computer vision applications,...
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Assessment of energy-efficient wireless network using autoencoders with unsupervised deep learning
The propagation of wireless networks in e-business applications demands efficient and robust anomaly detection techniques to ensure data security and...
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Inferencing transportation mode using unsupervised deep learning approach exploiting GPS point-level characteristics
Discovering the mode of transportation is a fundamental and challenging step in the various transportation analysis problems such as travel demand...
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Multi-level self attention for unsupervised learning person re-identification
In recent years, the task of person re-identification (ReID) has placed a critical demand on accurately describing image features. Attention...
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Superpixel Driven Unsupervised Deep Image Super-Resolution
Most of the existing deep learning-based image super-resolution methods require a large number of datasets or ground truth. However, these methods...
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Iterative unsupervised deep bilateral texture filtering
Texture filtering attempts to retain salient structures and remove insignificant textures. In this paper, we propose a highly effective iterative...
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Federated unsupervised representation learning
To leverage the enormous amount of unlabeled data on distributed edge devices, we formulate a new problem in federated learning called federated...
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Forged document detection and writer identification through unsupervised deep learning approach
In recent years, there has been a significant increase in document forgery, which includes the fraudulent replication of currency, diplomas, and...
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I2DKPCN: an unsupervised deep learning network
In this paper, we proposed an incremental two-dimensional kernel PCA-based convolutional network (I2DKPCN) which is a novel unsupervised deep...
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Unsupervised feature learning based on autoencoder for epileptic seizures prediction
Epilepsy is one of the most common neurological diseases in the world. It’s essential to predict epileptic seizures since it can provide patients...
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Deep Learning-Empowered Unsupervised Maritime Anomaly Detection
Automatically detecting anomalous vessel behaviour is an extremely crucial problem in intelligent maritime surveillance. In this paper, a deep...