Opposition-based Learning (OBL) is a new concept in machine learning, inspired from the
opposite relationship among entities. In 2005, for the first time the concept of opposition was …

Diverse forms of opposition are already existent virtually everywhere around us, and utilizing
opposite numbers to accelerate an optimization method is a new idea. Since 2005 …

In mammography diagnosis systems, high False Negative Rate (FNR) has always been a
significant problem since a false negative answer may lead to a patient's death. This paper …

Classification of breast abnormalities such as masses is a challenging task for radiologists.
Computer-aided Diagnosis (CADx) technology may enhance the performance of …

The concept of opposition-based learning (OBL) can be categorized into Type-I and Type-II
OBL methodologies. The Type-I OBL is based on the opposite points in the variable space …

An accurate and efficient computer-aided mammography diagnosis system plays an
important role as a second opinion to assist radiologists. Finding an accurate and robust …

Mammography is the most perceptive method for the detection of early breast cancer. The
abnormalities of breast are analyzed by digital mammogram images and the most important …

The most significant health problem in the world is breast cancer and early detection is the
key to predict it. Mammography is the most reliable method to diagnose breast cancer at the …

In this paper, the classification of microcalcification in digital mammogram based on
statistical features and Stochastic Neighbor Embedding (SNE) technique is proposed. The …

Breast cancer is the most common malignancy of women and is the second most common
and leading cause of cancer deaths among them. At present, there are no effective ways to …