[HTML][HTML] A survey on optical character recognition for Bangla and Devanagari scripts
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 …
recognition (OCR) for Roman, Chinese, and Japanese scripts. A lot of work has been also …
A Literature Survey on Handwritten Character Recognition
L Singh, JK Sandhu, R Sahu - … International Conference on …, 2023 - ieeexplore.ieee.org
Handwritten character Recognition has created a notable attention in the field of pattern
recognition and in machine learning. Text Recognition and document Recognition have …
recognition and in machine learning. Text Recognition and document Recognition have …
Predicting size of forest fire using hybrid model
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 …
meteorological and forest weather index (FWI) variables such as Fine Fuel Moisture Code …
Sinhala handwritten character recognition using convolutional neural network
J Mariyathas, V Shanmuganathan… - 2020 5th …, 2020 - ieeexplore.ieee.org
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 …
create a character recognition model for south Asian languages because of its shape and …
Hindi character recognition using RBF neural network and directional group feature extraction technique
D Singh, JP Saini, DS Chauhan - … International Conference on …, 2015 - ieeexplore.ieee.org
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 …
directional values of gradient features for handwritten Hindi character recognition. The …
Hindi handwritten character recognition using multiple classifiers
Humans can easily recognize handwritten words, after gaining basic knowledge of
languages. This knowledge needs to be transferred to computers for automatic character …
languages. This knowledge needs to be transferred to computers for automatic character …
Hindi handwritten character recognition using deep convolution neural network
D Chaudhary, K Sharma - 2019 6th international conference on …, 2019 - ieeexplore.ieee.org
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 …
Machine Learning (ML) problems, especially in multiclass image classification. With the …
Object detection and classification using machine learning techniques: a comparison of haar cascades and neural networks
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 …
computers the ability to perceive and respond to the world around them. This is a very useful …
[PDF][PDF] A professional comparison of c4. 5, mlp, svm for network intrusion detection based feature analysis
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 …
great financial loss. Intrusion Detection Systems (IDSs) is one of the main solutions for …
[PDF][PDF] Robust offline Gurmukhi handwritten character recognition using multilayer histogram oriented gradient features
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 …
characters is a challenging problem and is considered to be more significant than the …