Geetha Guttikonda - Academia.edu (original) (raw)

Papers by Geetha Guttikonda

2019 International Conference on Intelligent Computing and Control Systems (ICCS), 2019

2019 3rd International Conference on Computing Methodologies and Communication (ICCMC), 2019

This paper deals with the diabetes prediction by applying the relevant data mining techniques. Th... more This paper deals with the diabetes prediction by applying the relevant data mining techniques. The goal of data mining is extract desired knowledge from the information that is stored in the dataset and also for analyzing the data patterns. In this civilization, humans are facing number of health problems and they are not aware of their symptoms. One of such health problems is Diabetes Mellitus. Now a day’s, even the adults are suffering with this problem. In this paper, we have used predictive analysis in HUE to foresee the diseases that are persistent in nature. Here, the dataset is collected from the Pima Indian database. This framework along with SVM Classification gives an effective method to count the number of persons who are suffering from diabetes.

International Journal on Computational Science & Applications, 2015

2018 Fourth International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB), 2018

Decision tree algorithm is most popular for classification in machine learning and uses discrete ... more Decision tree algorithm is most popular for classification in machine learning and uses discrete data for classification. Information gain or Gini index is used for the entropy calculation in order to classify the given data. Decision tree can be implemented in several programming languages and many data mining tools uses this algorithm. Every implementation has its own advantages and disadvantages. To understand the difference between two implementations R-studio and Java. This paper explains about two different implementation methods gives the best one among two. We mainly focus on pros and cons of these two implementation methods

Automated Traffic sign board classification system is one of the key technologies of Intelligent ... more Automated Traffic sign board classification system is one of the key technologies of Intelligent Transportation Systems (ITS). Traffic Surveillance System is being more and important with improving urban scale and increasing number of vehicles. This Paper presents an intelligent sign board classification method based on blob analysis in traffic surveillance. Processing is done by three main steps: moving object segmentation, blob analysis, and classifying. A Sign board is modelled as a rectangular patch and classified via blob analysis. By processing the blob of sign boards, the meaningful features are extracted. Tracking moving targets is achieved by comparing the extracted features with training data. After classifying the sign boards the system will intimate to user in the form of alarms, sound waves. The experimental results show that the proposed system can provide real-time and useful information for traffic surveillance.

Gender classification has become an essential task in human computer interaction (HCI). Gender cl... more Gender classification has become an essential task in human computer interaction (HCI). Gender classification is used in immense number of applications like passive surveillance, control in smart buildings (restricting access to certain areas based on gender) and supermarkets, gender advertising, security investigation. So far detection of gender using facial features is done by using the methods like Gabor wavelets, artificial neural networks and support vector machine. In this work, facial distance measure is used as a progenitor to achieve the gender classification. The proposed approach performs gender classification using mathematical operations on the frontal pose face images using Matlab. This work can be further evaluated in future by using different databases with various poses other than the frontal pose.

2019 International Conference on Intelligent Computing and Control Systems (ICCS), 2019

2019 3rd International Conference on Computing Methodologies and Communication (ICCMC), 2019

This paper deals with the diabetes prediction by applying the relevant data mining techniques. Th... more This paper deals with the diabetes prediction by applying the relevant data mining techniques. The goal of data mining is extract desired knowledge from the information that is stored in the dataset and also for analyzing the data patterns. In this civilization, humans are facing number of health problems and they are not aware of their symptoms. One of such health problems is Diabetes Mellitus. Now a day’s, even the adults are suffering with this problem. In this paper, we have used predictive analysis in HUE to foresee the diseases that are persistent in nature. Here, the dataset is collected from the Pima Indian database. This framework along with SVM Classification gives an effective method to count the number of persons who are suffering from diabetes.

International Journal on Computational Science & Applications, 2015

2018 Fourth International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB), 2018

Decision tree algorithm is most popular for classification in machine learning and uses discrete ... more Decision tree algorithm is most popular for classification in machine learning and uses discrete data for classification. Information gain or Gini index is used for the entropy calculation in order to classify the given data. Decision tree can be implemented in several programming languages and many data mining tools uses this algorithm. Every implementation has its own advantages and disadvantages. To understand the difference between two implementations R-studio and Java. This paper explains about two different implementation methods gives the best one among two. We mainly focus on pros and cons of these two implementation methods

Automated Traffic sign board classification system is one of the key technologies of Intelligent ... more Automated Traffic sign board classification system is one of the key technologies of Intelligent Transportation Systems (ITS). Traffic Surveillance System is being more and important with improving urban scale and increasing number of vehicles. This Paper presents an intelligent sign board classification method based on blob analysis in traffic surveillance. Processing is done by three main steps: moving object segmentation, blob analysis, and classifying. A Sign board is modelled as a rectangular patch and classified via blob analysis. By processing the blob of sign boards, the meaningful features are extracted. Tracking moving targets is achieved by comparing the extracted features with training data. After classifying the sign boards the system will intimate to user in the form of alarms, sound waves. The experimental results show that the proposed system can provide real-time and useful information for traffic surveillance.

Gender classification has become an essential task in human computer interaction (HCI). Gender cl... more Gender classification has become an essential task in human computer interaction (HCI). Gender classification is used in immense number of applications like passive surveillance, control in smart buildings (restricting access to certain areas based on gender) and supermarkets, gender advertising, security investigation. So far detection of gender using facial features is done by using the methods like Gabor wavelets, artificial neural networks and support vector machine. In this work, facial distance measure is used as a progenitor to achieve the gender classification. The proposed approach performs gender classification using mathematical operations on the frontal pose face images using Matlab. This work can be further evaluated in future by using different databases with various poses other than the frontal pose.