A comprehensive survey of image segmentation: clustering methods, performance parameters, and benchmark datasets
Image segmentation is an essential phase of computer vision in which useful information is
extracted from an image that can range from finding objects while moving across a room to …
extracted from an image that can range from finding objects while moving across a room to …
From classical to soft computing based watermarking techniques: A comprehensive review
With evolution of digital technology, it is challenging to protect personal data from access
without consent. Digital watermarking conceals some information as watermark to protect …
without consent. Digital watermarking conceals some information as watermark to protect …
Gravitational search algorithm: a comprehensive analysis of recent variants
Gravitational search algorithm is a nature-inspired algorithm based on the mathematical
modelling of the Newton's law of gravity and motion. In a decade, researchers have …
modelling of the Newton's law of gravity and motion. In a decade, researchers have …
A survey on the utilization of Superpixel image for clustering based image segmentation
Superpixel become increasingly popular in image segmentation field as it greatly helps
image segmentation techniques to segment the region of interest accurately in noisy …
image segmentation techniques to segment the region of interest accurately in noisy …
DeepBatch: A hybrid deep learning model for interpretable diagnosis of breast cancer in whole-slide images
The gold standard for breast cancer diagnosis, treatment, and management is the
histological analysis of a suspected section. Histopathology consists in analyzing the …
histological analysis of a suspected section. Histopathology consists in analyzing the …
A new complete color normalization method for H&E stained histopatholgical images
S Vijh, M Saraswat, S Kumar - Applied Intelligence, 2021 - Springer
The popularity of digital histopathology is growing rapidly in the development of computer
aided disease diagnosis systems. However, the color variations due to manual cell …
aided disease diagnosis systems. However, the color variations due to manual cell …
Improved convolutional neural network based histopathological image classification
V Rachapudi, G Lavanya Devi - Evolutionary Intelligence, 2021 - Springer
Histopathological image classification is one of the important application areas of medical
imaging. However, an accurate and efficient classification is still an open-ended research …
imaging. However, an accurate and efficient classification is still an open-ended research …
A new recommendation system using map-reduce-based tournament empowered Whale optimization algorithm
AK Tripathi, H Mittal, P Saxena, S Gupta - Complex & Intelligent Systems, 2021 - Springer
In the era of Web 2.0, the data are growing immensely and is assisting E-commerce
websites for better decision-making. Collaborative filtering, one of the prominent …
websites for better decision-making. Collaborative filtering, one of the prominent …
[PDF][PDF] Breast cancer nuclei segmentation and classification based on a deep learning approach
M Kowal, M Skobel, A Gramacki… - International Journal of …, 2021 - intapi.sciendo.com
One of the most popular methods in the diagnosis of breast cancer is fine-needle biopsy
without aspiration. Cell nuclei are the most important elements of cancer diagnostics based …
without aspiration. Cell nuclei are the most important elements of cancer diagnostics based …
Breast cancer intelligent analysis of histopathological data: A systematic review
FA Zeiser, CA da Costa, AV Roehe… - Applied Soft …, 2021 - Elsevier
For a favorable prognosis of breast cancer, early diagnosis is essential. The
histopathological analysis is considered the gold standard to indicate the type of cancer …
histopathological analysis is considered the gold standard to indicate the type of cancer …