In the past five years, 7.8 million women were diagnosed with breast cancer. Breast cancer is curable if it is discovered in early stages. Therefore, mammography screening is essential. But, since interpretation can prove difficult, various automated interpretation systems have been proposed so far. A crucial step of the interpretation process is segmentation: identifying…
Combining cellular automata (CA) with convolutional neural networks (CNN) has been overtime an important topic of scientific interest in the field of computer vision. This has been due to the high number of common aspects between the two models, such as extracting information and making decision based on pixel neighbourhoods. While there are many…
Breast cancer is the most frequent type of malignancy in women, with 2.3 million diagnostics only in 2020. However, as a consequence of early diagnosis and appropriate treatment, more and more women are being cured. Among screening methods, mammography is one of the most used, and segmentation is a crucial step of its analysis.…
Breast cancer is the most common type of cancer found in women. One of the most effiective methods for early identification of breast cancer is the mammogram. Numerous computer-aided systems for detecting breast cancer from mammograms have been introduced. In this paper, we present a new way for combining Cellular Automata with Fuzzy Logic,…
Brain disorders are becoming more prevalent, and accurate brain segmentation is a vital component of identifying the appropriate treatment. This study introduces an enhanced graph-based image segmentation technique. The node selection process involves creating an ellipsoid centered at the image’s center of mass. The proposed approach is evaluated using the NFBS dataset and demonstrates…
Between 2015 and 2020, 7.8 million women were diagnosed with breast cancer. If the cancer is discovered early, it can be completely cured. Computer-aided detection and diagnosis systems are a helpful tool. We propose such a system: after pre-processing the mammography, the region of interest is identified using an unsupervised manner. Textural features are…
Automating artificial intelligence (AI) model training has emerged as a significant challenge in the field of automation. The complete pipeline from raw data to model deployment poses the need to define robust processes that ensure the efficiency of the services that expose the models. This paper introduces a generic architecture for automating data preparation,…
The field of Artificial Intelligence (AI) has rapidly transformed from a buzzword technology to a fundamental aspect of numerous industrial software applications. However, this quick transition has not allowed for the development of robust best practices for designing and implementing processes related to data engineering, machine learning (ML)-based model training, deployment, monitoring, and maintenance.…
On account of the extreme expansion of the scientific research paper databases, the usage of searching and recommender systems in this area increased, as they can help researchers find appropriate papers by searching in enormous indexed datasets. Depending on where the papers are published, there might be stricter policies that force the author to…
Malicious links are becoming the main propagating vector for web-malware. They may lead to serious security issues, such as phishing, distribution of fake news and low-quality content, drive-by-downloads, and malicious code running. Malware link detection is a challenging domain because of the dynamics of the on-line environment, where web links and web content are…