Trends in digital image processing of isolated microalgae by incorporating classification algorithm
Identification of microalgae species is of importance due to the uprising of harmful algae
blooms affecting both the aquatic habitat and human health. Despite this occurence …
blooms affecting both the aquatic habitat and human health. Despite this occurence …
Deploying machine and deep learning models for efficient data-augmented detection of COVID-19 infections
A Sedik, AM Iliyasu, B Abd El-Rahiem… - Viruses, 2020 - mdpi.com
This generation faces existential threats because of the global assault of the novel Corona
virus 2019 (ie, COVID-19). With more than thirteen million infected and nearly 600000 …
virus 2019 (ie, COVID-19). With more than thirteen million infected and nearly 600000 …
LCD-capsule network for the detection and classification of lung cancer on computed tomography images
Lung cancer is the second most prominent cancer in men and women, and it is also the
leading cause of cancer-related mortality. If lung cancer is diagnosed early, when it is …
leading cause of cancer-related mortality. If lung cancer is diagnosed early, when it is …
Efficient high-dimension feature selection based on enhanced equilibrium optimizer
S Ouadfel, M Abd Elaziz - Expert Systems with Applications, 2022 - Elsevier
Feature selection (FS) is an important task in any classification process and aims to choose
the smallest features number that yields higher classification accuracy. FS can be formulated …
the smallest features number that yields higher classification accuracy. FS can be formulated …
Detection and classification of gastrointestinal disease using convolutional neural network and SVM
Gastrointestinal tract is a series of hollow organs connected in a long tube twisting from the
mouth to the anus. Recovery of gastrointestinal diseased patients depends on the early …
mouth to the anus. Recovery of gastrointestinal diseased patients depends on the early …
Boosting capuchin search with stochastic learning strategy for feature selection
The technological revolution has made available a large amount of data with many
irrelevant and noisy features that alter the analysis process and increase time processing …
irrelevant and noisy features that alter the analysis process and increase time processing …
Medical image fusion based on improved multi-scale morphology gradient-weighted local energy and visual saliency map
Y Zhang, M Jin, G Huang - Biomedical Signal Processing and Control, 2022 - Elsevier
Medical image fusion refers to the process of fusing images of different modes of the same
object using image processing technology to maximize the mining of image information and …
object using image processing technology to maximize the mining of image information and …
[HTML][HTML] Adaptive diagnostic machine learning technique for classification of cell decisions for AKT protein
Artificial intelligence techniques can unravel clinically consistent information in clinical data
which in turn assist in decision-making. With the help of state-of-the-art techniques …
which in turn assist in decision-making. With the help of state-of-the-art techniques …
Detection of corona virus disease using a novel machine learning approach
AO Salau - 2021 international conference on decision aid …, 2021 - ieeexplore.ieee.org
In recent times, Coronavirus Disease 2019 (COVID-19) has become a growing concern
which has taken the world by surprise. Early detection of this virus can be used to save …
which has taken the world by surprise. Early detection of this virus can be used to save …
Osteoporosis diagnosis in knee X-rays by transfer learning based on convolution neural network
Osteoporosis degrades the quality of bones and is the primary cause of fractures in the
elderly and women after menopause. The high diagnostic and treatment costs urge the …
elderly and women after menopause. The high diagnostic and treatment costs urge the …