7 citations · 11 across the 11 of their papers we have counts for
11 papers
CASISR: Circular Arbitrary-Scale Image Super-Resolution
Honggui Li, Zhengyang Zhang, Dingtai Li +11
The generalization performance (GP) of deep learning-based arbitrary-scale image super-resolution (ASISR) methods is subject to limited training datasets and unlimited testing data…
CECGSR: Circular ECG Super-Resolution
Honggui Li, Zhengyang Zhang, Dingtai Li +11
Background and Objective: The electrocardiogram (ECG) plays a crucial role in the diagnosis and treatment of various cardiac diseases. ECG signals suffer from low-resolution (LR) d…
CIC: Circular Image Compression
Honggui Li, Sinan Chen, Dingtai Li +9
Learned image compression (LIC) is currently the cutting-edge method. However, the inherent difference between testing and training images of LIC results in performance degradation…
CMISR: Circular Medical Image Super-Resolution
Honggui Li, Nahid Md Lokman Hossain, Maria Trocan +2
Classical methods of medical image super-resolution (MISR) utilize open-loop architecture with implicit under-resolution (UR) unit and explicit super-resolution (SR) unit. The UR u…
CSwin2SR: Circular Swin2SR for Compressed Image Super-Resolution
Honggui Li, Maria Trocan, Mohamad Sawan +1
Closed-loop negative feedback mechanism is extensively utilized in automatic control systems and brings about extraordinary dynamic and static performance. In order to further impr…
A Review of Resource Management in Fog Computing: Machine Learning Perspective
Muhammad Fahimullah, Shohreh Ahvar, Maria Trocan
Fog computing becomes a promising technology to process user's requests near the proximity of users to reduce response time for latency-sensitive requests. Despite its advantages,…
ICRICS: Iterative Compensation Recovery for Image Compressive Sensing
Honggui Li, Maria Trocan, Dimitri Galayko +1
Closed-loop architecture is widely utilized in automatic control systems and attain distinguished performance. However, classical compressive sensing systems employ open-loop archi…
Patch Selection for Melanoma Classification
Guillaume Lachaud, Patricia Conde-Cespedes, Maria Trocan
In medical image processing, the most important information is often located on small parts of the image. Patch-based approaches aim at using only the most relevant parts of the im…
A Practical guide on Explainable AI Techniques applied on Biomedical use case applications
Adrien Bennetot, Ivan Donadello, Ayoub El Qadi +10
Last years have been characterized by an upsurge of opaque automatic decision support systems, such as Deep Neural Networks (DNNs). Although they have great generalization and pred…
Cascade Decoders-Based Autoencoders for Image Reconstruction
Honggui Li, Dimitri Galayko, Maria Trocan +1
Autoencoders are composed of coding and decoding units, hence they hold the inherent potential of high-performance data compression and signal compressed sensing. The main disadvan…
Explaining Credit Risk Scoring through Feature Contribution Alignment with Expert Risk Analysts
Ayoub El Qadi, Natalia Diaz-Rodriguez, Maria Trocan +1
Credit assessments activities are essential for financial institutions and allow the global economy to grow. Building robust, solid and accurate models that estimate the probabilit…