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A study on RGB image multi-thresholding using Kapur/Tsallis entropy and moth-flame algorithm
(Universidad Internacional de la Rioja, 2021)
In the literature, a considerable number of image processing and evaluation procedures are proposed and
implemented in various domains due to their practical importance. Thresholding is one of the pre-processing
techniques, ...
A New Model for Brain Tumor Detection Using Ensemble Transfer Learning and Quantum Variational Classifier
(Computational Intelligence and Neuroscience, 2022)
A brain tumor is an abnormal enlargement of cells if not properly diagnosed. Early detection of a brain tumor is critical for clinical practice and survival rates. Brain tumors arise in a variety of shapes, sizes, and ...
G-Sep: A Deep Learning Algorithm for Detection of Long-Term Sepsis Using Bidirectional Gated Recurrent Unit
(International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, 2022)
Sepsis is a common and deadly condition that must be treated eloquently within 19 hours. Numerous deep learning techniques, including Recurrent Neural Networks, Convolution Neural Networks, Long Short-Term Memory, and Gated ...
A Framework for Extractive Text Summarization Based on Deep Learning Modified Neural Network Classifier
(Association for Computing Machinery, 2021)
There is an exponential growth of text data over the internet, and it is expected to gain significant growth and attention in the coming years. Extracting meaningful insights from text data is crucially important as it ...
CNN supported framework for automatic extraction and evaluation of dermoscopy images
(Journal of Supercomputing, 2022)
Skin Cancer is one of the acute diseases listed under top 5 groups in 2020 report of World Health Organisation. This research aims to propose a Convolutional Neural Network framework to extract and evaluate the suspicious ...
An Integrated Framework for COVID-19 Classification Based on Ensembles of Deep Features and Entropy Coded GLEO Feature Selection
(International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2023)
COVID-19 is a challenging worldwide pandemic disease nowadays that spreads from person to person in a very fast manner. It is necessary to develop an automated technique for COVID-19 identification. This work investigates ...
Automated segmentation of leukocyte from hematological images—a study using various CNN schemes
(Springer, 2022)
Medical images play a fundamental role in disease screening, and automated evaluation of these images is widely preferred in hospitals. Recently, Convolutional Neural Network (CNN) supported medical data assessment is ...
Automated detection of age-related macular degeneration using a pre-trained deep-learning scheme
(Springer, 2022)
An eye disease affects the entire sensory operation, and an unrecognised and untreated eye disease may lead to loss of vision. The proposed work aims to develop an automated age-related macular degeneration (AMD) detection ...
Analysis of the Pertinence of Indian Women's Institutions in Collaborative Research
(IEEE Transactions on Computational Social Systems, 2023)
Nowadays, the relevance of women-only educational institutes is questionable due to various reasons that include social uplifting, ample opportunities, and a free mindset among the population. Though women colleges and ...
Detection of anomaly in surveillance videos using quantum convolutional neural networks
(Image and Vision Computing, 2023)
Anomalous behavior identification is the process of detecting behavior that differs from its normal. These incidents will vary from violence to war, road crashes to kidnapping, and so on in a surveillance model. Video ...