A novel multistage transfer learning for ultrasound breast cancer image classification
Breast cancer diagnosis is one of the many areas that has taken advantage of artificial
intelligence to achieve better performance, despite the fact that the availability of a large …
intelligence to achieve better performance, despite the fact that the availability of a large …
An improved marine predators algorithm with fuzzy entropy for multi-level thresholding: real world example of COVID-19 CT image segmentation
Medical imaging techniques play a critical role in diagnosing diseases and patient
healthcare. They help in treatment, diagnosis, and early detection. Image segmentation is …
healthcare. They help in treatment, diagnosis, and early detection. Image segmentation is …
Voxelated opto-physically unclonable functions via irreplicable wrinkles
The increased prevalence of the Internet of Things (IoT) and the integration of digital
technology into our daily lives have given rise to heightened security risks and the need for …
technology into our daily lives have given rise to heightened security risks and the need for …
Improving automated visual fault inspection for semiconductor manufacturing using a hybrid multistage system of deep neural networks
In the semiconductor industry, automated visual inspection aims to improve the detection
and recognition of manufacturing defects by leveraging the power of artificial intelligence …
and recognition of manufacturing defects by leveraging the power of artificial intelligence …
Improved artificial bee colony using sine-cosine algorithm for multi-level thresholding image segmentation
Multilevel-thresholding is an efficient method used in image segmentation. This paper
presents a hybrid meta-heuristic approach for multi-level thresholding image segmentation …
presents a hybrid meta-heuristic approach for multi-level thresholding image segmentation …
Explainable ResNet50 learning model based on copula entropy for cotton plant disease prediction
This paper presents a novel Deep Learning (DL) framework for cotton plant disease
prediction based on Explainable Artificial Intelligence (XAI) and Copula entropy based-Grey …
prediction based on Explainable Artificial Intelligence (XAI) and Copula entropy based-Grey …
[KSIĄŻKA][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 …
A survey on the energy detection of OFDM signals with dynamic threshold adaptation: Open Issues and Future Challenges
Cognitive radio (CR), as a concept based on the ability to detect and share the unutilised
spectrum, has been envisioned as a promising candidate to improve the efficiency of …
spectrum, has been envisioned as a promising candidate to improve the efficiency of …
[HTML][HTML] ASR crack identification in bridges using deep learning and texture analysis
Abstract Alkali-Silica Reaction (ASR), commonly known as 'concrete cancer,'is an expansive
reaction occurring over time between aggregate constituents and alkaline hydroxides from …
reaction occurring over time between aggregate constituents and alkaline hydroxides from …
Sugeno integral generalization applied to improve adaptive image binarization
Classic adaptive binarization methodologies threshold pixels intensity with respect to
adjacent pixels exploiting integral images. In turn, integral images are generally computed …
adjacent pixels exploiting integral images. In turn, integral images are generally computed …