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An overview of biomedical image analysis from the deep learning perspective
S Chakraborty, K Mali - … machine intelligence in computer vision and …, 2020 - igi-global.com
Biomedical image analysis methods are gradually shifting towards computer-aided solutions
from manual investigations to save time and improve the quality of the diagnosis. Deep …
from manual investigations to save time and improve the quality of the diagnosis. Deep …
Evaluation of recurrent neural network and its variants for intrusion detection system (IDS)
This article describes how sequential data modeling is a relevant task in Cybersecurity.
Sequences are attributed temporal characteristics either explicitly or implicitly. Recurrent …
Sequences are attributed temporal characteristics either explicitly or implicitly. Recurrent …
[HTML][HTML] A survey of the development of biomimetic intelligence and robotics
Biomimetics is the development of novel theories and technologies by emulating the models
and systems of nature. The transfer of function from biological science into engineering …
and systems of nature. The transfer of function from biological science into engineering …
[BOG][B] A beginner's guide to image preprocessing techniques
For optimal computer vision outcomes, attention to image pre-processing is required so that
one can improve image features by eliminating unwanted falsification. This book …
one can improve image features by eliminating unwanted falsification. This book …
SuFMoFPA: A superpixel and meta-heuristic based fuzzy image segmentation approach to explicate COVID-19 radiological images
Coronavirus disease 2019 or COVID-19 is one of the biggest challenges which are being
faced by mankind. Researchers are continuously trying to discover a vaccine or medicine for …
faced by mankind. Researchers are continuously trying to discover a vaccine or medicine for …
An efficient multilevel thresholding based satellite image segmentation approach using a new adaptive cuckoo search algorithm
It is the most challenging and difficult task to segment a satellite image because of its
complete randomness, multiple regions of interest, weak correlation with pixels, and regions …
complete randomness, multiple regions of interest, weak correlation with pixels, and regions …
Classification of mice hepatic granuloma microscopic images based on a deep convolutional neural network
Y Wang, Y Chen, N Yang, L Zheng, N Dey… - Applied Soft …, 2019 - Elsevier
Hepatic granuloma develops in the early stage of liver cirrhosis which can seriously injury
liver health. At present, the assessment of medical microscopic images is necessary for …
liver health. At present, the assessment of medical microscopic images is necessary for …
An unsupervised fuzzy clustering approach for early screening of COVID-19 from radiological images
A global pandemic scenario is witnessed worldwide owing to the menace of the rapid
outbreak of the deadly COVID-19 virus. To save mankind from this apocalyptic onslaught, it …
outbreak of the deadly COVID-19 virus. To save mankind from this apocalyptic onslaught, it …
Computer-aided diagnosis for burnt skin images using deep convolutional neural network
Numerous patients died every year due to the leading causes of deaths all over the world
and burn injuries are one of them. Burn injury cases are most viewed in low and middle …
and burn injuries are one of them. Burn injury cases are most viewed in low and middle …
RETRACTED ARTICLE: An improved approach for automatic spine canal segmentation using probabilistic boosting tree (PBT) with fuzzy support vector machine
Spine canal segmentation is an emerging zone in research proposed to help interpretation
and processing of advanced MRI and CT images. For instance, high resolution three …
and processing of advanced MRI and CT images. For instance, high resolution three …