The past few decades have witnessed an intensive research on optical character
recognition (OCR) for Roman, Chinese, and Japanese scripts. A lot of work has been also …

Handwritten character Recognition has created a notable attention in the field of pattern
recognition and in machine learning. Text Recognition and document Recognition have …

This paper outlines a hybrid approach in data mining to predict the size of forest fire using
meteorological and forest weather index (FWI) variables such as Fine Fuel Moisture Code …

Handwritten character recognition is widely used for the English language. It is difficult to
create a character recognition model for south Asian languages because of its shape and …

In this paper, Radial Basis Function (RBF) neural Network has been implemented on eight
directional values of gradient features for handwritten Hindi character recognition. The …

Humans can easily recognize handwritten words, after gaining basic knowledge of
languages. This knowledge needs to be transferred to computers for automatic character …

Convolution Neural Network (CNN) is turning out to be a very powerful tool for solving
Machine Learning (ML) problems, especially in multiclass image classification. With the …

Object recognition and object detection are sub fields of computer vision, the task of giving
computers the ability to perceive and respond to the world around them. This is a very useful …

The volume of targeted network attacks is increasing continuously over time. This causes
great financial loss. Intrusion Detection Systems (IDSs) is one of the main solutions for …

Accept: 19/Jun/2018, Published: 30/Jun/2018 Abstract-Recognizing offline handwritten
characters is a challenging problem and is considered to be more significant than the …