since most common form of cervical cancer starts with pre-cancerous changes, a flawless detection of these changes becomes an important issue to prevent and treat the cervix cancer. there are 2 ways to stop this disease from developing. one way is to find and treat pre-cancers before they become true cancers, and the other is to prevent the pre-cancers in the first place. the presented approach...

Geological facies interpretation is essential for reservoir studying. The method of classification and identification seismic traces is a powerful approach for geological facies classification and distinction. Use of neural networks as classifiers is increasing in different sciences like seismic. They are computer efficient and ideal for patterns identification. They can simply learn new algori...

We present Self-Classifier – a novel self-supervised end-to-end classification learning approach. learns labels and representations simultaneously in single-stage manner by optimizing for same-class prediction of two augmented views the same sample. To guarantee non-degenerate solutions (i.e., where all are assigned to class) we propose mathematically motivated variant cross-entropy loss that h...

glaucoma, a group of multifactor ocular diseases, is the second leading cause of blindness worldwide. primary open angle (poa) is the most common type of glaucoma, characterized by progressive optic nerve degeneration. numerous genes and proteins have been revealed to be associated with poag, but the pathologic mechanisms of the disease are still poorly understood. proteomics, the collective st...

The classification of various document images is considered an important step towards building a modern digital library or office automation system. Convolutional Neural Network (CNN) classifiers trained with backpropagation are considered to be the current state of the art model for this task. However, there are two major drawbacks for these classifiers: the huge computational power demand for...

A hybrid approach for intrusion detection in computer networks is presented in this paper. The proposed approach combines an evolutionary-based fuzzy system with an Ant Colony Optimization procedure to generate high-quality fuzzy-classification rules. We applied our hybrid learning approach to network security and validated it using the DARPA KDD-Cup99 benchmark data set. The results indicate t...