Advances in data preprocessing for biomedical data fusion: An overview of the methods, challenges, and prospects
Due to the proliferation of biomedical imaging modalities, such as Photoacoustic
Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc …
Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc …
The Role of generative adversarial network in medical image analysis: An in-depth survey
M AlAmir, M AlGhamdi - ACM Computing Surveys, 2022 - dl.acm.org
A generative adversarial network (GAN) is one of the most significant research directions in
the field of artificial intelligence, and its superior data generation capability has garnered …
the field of artificial intelligence, and its superior data generation capability has garnered …
Seismic shot gather denoising by using a supervised-deep-learning method with weak dependence on real noise data: A solution to the lack of real noise data
In recent years, supervised-deep-learning methods have shown some advantages over
conventional methods in seismic data denoising, such as higher signal-to-noise ratio after …
conventional methods in seismic data denoising, such as higher signal-to-noise ratio after …
Augmented data driven self-attention deep learning method for imbalanced fault diagnosis of the HVAC chiller
C Shen, H Zhang, S Meng, C Li - Engineering Applications of Artificial …, 2023 - Elsevier
The chiller fault diagnosis is of great significance to maintain the normal operation of the
HVAC system and indoor comfort. Due to the difficulty in collecting the chiller's fault data, we …
HVAC system and indoor comfort. Due to the difficulty in collecting the chiller's fault data, we …
Generative adversarial network based data augmentation for CNN based detection of Covid-19
Covid-19 has been a global concern since 2019, crippling the world economy and health.
Biological diagnostic tools have since been developed to identify the virus from bodily fluids …
Biological diagnostic tools have since been developed to identify the virus from bodily fluids …
Deep learning data augmentation for Raman spectroscopy cancer tissue classification
Abstract Recently, Raman Spectroscopy (RS) was demonstrated to be a non-destructive
way of cancer diagnosis, due to the uniqueness of RS measurements in revealing molecular …
way of cancer diagnosis, due to the uniqueness of RS measurements in revealing molecular …
Recent advances in generative adversarial networks for gene expression data: a comprehensive review
M Lee - Mathematics, 2023 - mdpi.com
The evolving field of generative artificial intelligence (GenAI), particularly generative deep
learning, is revolutionizing a host of scientific and technological sectors. One of the pivotal …
learning, is revolutionizing a host of scientific and technological sectors. One of the pivotal …
Rapid diagnosis of Covid-19 infections by a progressively growing GAN and CNN optimisation
Background and objective Covid-19 infections are spreading around the globe since
December 2019. Several diagnostic methods were developed based on biological …
December 2019. Several diagnostic methods were developed based on biological …
A survey of synthetic data generation for machine learning
M Abufadda, K Mansour - 2021 22nd international arab …, 2021 - ieeexplore.ieee.org
Data is the fuel of machine learning algorithms, therefore data generation in machine
learning is becoming an important topic. The problem is that finding enough data for …
learning is becoming an important topic. The problem is that finding enough data for …
Attribute reduction based on neighborhood constrained fuzzy rough sets
M Hu, Y Guo, D Chen, ECC Tsang, Q Zhang - Knowledge-Based Systems, 2023 - Elsevier
The construction of fuzzy relations is a key issue of fuzzy rough sets. The fuzzy relations
generated by the soft distances between samples are more robust than that generated by …
generated by the soft distances between samples are more robust than that generated by …