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Author

Anandi Giridharan

Bio: Anandi Giridharan is an academic researcher from Indian Institute of Science. The author has contributed to research in topics: Node (networking) & Mobile agent. The author has an hindex of 3, co-authored 11 publications receiving 20 citations.

Papers
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Proceedings ArticleDOI
01 Oct 2019
TL;DR: The proposed model uses Convolutional Neural Networks to predict and classify seven different types of skin lesions and is based on the experiment conducted using the MNIST:HAM10000 dataset which consists of 10000 labelled images.
Abstract: The usage of Deep Learning has immensely increased in the present years. Convolutional Neural Networks, Recurrent Neural Networks, Generative Adversarial Networks, Variational Auto Encoders are among the prominent architectures in Deep Learning. Convolutional Neural Networks architecture has signified high accuracy and performance for image classification problems. On the other hand skin cancer if recognized or treated early is almost curable. The proposed model in the paper uses Convolutional Neural Networks to predict and classify seven different types of skin lesions. A website is developed for the real time usage of the model, which can predict the three most probable types of skin lesions for a given image. The observations and results are based on the experiment conducted using the MNIST:HAM10000 dataset which consists of 10000 labelled images.

29 citations

01 Sep 2007
TL;DR: In this article, the authors have designed a Technical Educational Quality Assurance and Assessment (TEQ-AA) system, which makes use of the information on the web and analyzes the standards of the institution.
Abstract: Engineering education quality embraces the activities through which a technical institution satisfies itself that the quality of education it provi des and standards it has set are appropriate and are being maintained. There is a need to develop a standardis ed approach to most aspects of quality assurance for engineering programmes which is sufficiently well defined to be accepted for all assessments. We have designed a Technical Educational Quality Assurance and Assessment (TEQ-AA) System, which makes use of the information on the web and analyzes the standards of the institution. With the standards as anchors for definition, the institution is clearer about its present in order to plan better for its future and enhancing the level of educational quality. The system has been tested and implemented on the technical educational Institutions in the Karnataka State which usually host their web pages for commercially advertising their technical education programs and their Institution objectives, policies, etc., for commerc ialization and for better reach-out to the students and facult y. This helps in assisting the students in selecting an ins titution for study and to assist in employment.

6 citations

Proceedings ArticleDOI
07 Nov 2002
TL;DR: A subject model for a Web-based education system that facilitates distance education is proposed and uses a tree with multiple links that has been very useful in guiding diverse students through the courseware.
Abstract: With the rapid growth of the Internet, its users and its applications, there has been considerable interest in Web-based education systems that facilitates distance education. We propose a subject model for a Web-based education system. The designed model uses a tree with multiple links. Each link weight has been derived from relationships among the concepts of the subject. The designed modular tree with multiple conceptual links has been very useful in guiding diverse students through the courseware.

4 citations

Journal ArticleDOI
TL;DR: The purpose of this framework is to provide a formal basis for their performance evaluation and behavioral study of the SDP, where the external behavior of the system can be predicted and compared to a model of expected behavior from the original requirements.
Abstract: Service Discovery Protocol (SDP) is important in ubiquitous applications, where a large number of devices and software components collab orate unobtrusively and provide numerous services without user intervention. Existing service discovery schemes use a service matching process in order to offer services of interest to the users. Potentially, the context information of the users and surrou nding environment can be used to improve the quality of service matching. We propose a C -IOB (Context- Information, Observation and Belief) based service discovery model, which deals with the above challenges by processing the context information and by formulating the beliefs based on the basis of observations. With these formulated beliefs the required services will be provided to the users. In this work, we present an approach for automated validation of C-IOB based service discovery model in a typical u biquitous museum environment, where the external behavior of the system can be predicted and compared to a model of expected behavior from the original requirements. Formal specification using SDL (Specification and Description Language) based system has been used to conduct verification and validation of the system. The purpose of this framework is to provide a formal basis for their performance evaluation and behavioral study of the SDP.

2 citations

Proceedings ArticleDOI
16 Nov 2020
TL;DR: In this paper, the Food Classifier and Nutrition Interpreter (FCNI) is proposed, which is a user-friendly tool that classifies various food types with a different graphical representation of food nutrients values in terms of calorie estimation along with a multimedia audio response.
Abstract: Food plays a vital role in our day-to-day life to get all the required nutrients for a healthy lifestyle. In recent years, obesity has become one of the major concerns among humans. Therefore, it is necessary for each individual to keep track of the nutrition intake in order to have a balanced diet. This has scaled up the implementation of automatic food analysis and semantic food detection using different image classification approaches, among which Deep Learning has brought a series of breakthroughs in this field. We have proposed the Food Classifier and Nutrition Interpreter (FCNI), a user-friendly tool that classifies various food types with a different graphical representation of food nutrients values in terms of calorie estimation along with a multimedia audio response. FCNI improves state-of-the-art food detection by a considerable margin on achieving about 96.81% accuracy.

1 citations


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Journal ArticleDOI
TL;DR: A deep learning framework for skin cancer detection was applied to five state-of-art convolutional neural networks to create both a plain and a hierarchical (with 2 levels) classifiers that are capable to distinguish between seven types of moles.
Abstract: Skin diseases have become a challenge in medical diagnosis due to visual similarities. Although melanoma is the best-known type of skin cancer, there are other pathologies that are the cause of many death in recent years. The lack of large datasets is one of the main difficulties to develop a reliable automatic classification system. This paper presents a deep learning framework for skin cancer detection. Transfer learning was applied to five state-of-art convolutional neural networks to create both a plain and a hierarchical (with 2 levels) classifiers that are capable to distinguish between seven types of moles. The HAM10000 dataset, a large collection of dermatoscopic images, were used for experiments, with the help of data augmentation techniques to improve performance. Results demonstrate that the DenseNet201 network is suitable for this task, achieving high classification accuracies and F-measures with lower false negatives. The plain model performed better than the 2-levels model, although the first level, i.e. a binary classification, between nevi and non-nevi yielded the best outcomes.

55 citations

Journal ArticleDOI
TL;DR: In this paper , the authors proposed Eff2Net, which is built on EfficientNetV2 in conjunction with the Efficient Channel Attention (ECA) block and achieved an overall testing accuracy of 84.70%.

28 citations

Proceedings ArticleDOI
01 Dec 2016
TL;DR: The present work introduces a framework for an automated information system that manages the quality assurance in higher educations institutions and provides an automation tool that avoids unnecessary and redundant tasks associated to quality in higher education institutions.
Abstract: Despite the great efforts to assure quality in higher education institutions, the ambiguity of its related concepts and requirements constitute a big challenge when trying to implement it as an automated information system. The present work introduces a framework for an automated information system that manages the quality assurance in higher educations institutions. The aim of designing such a system is to provide an automation tool that avoids unnecessary and redundant tasks associated to quality in higher education institutions. In addition, the proposed system helps all higher education stockholders to handle and monitor their tasks. Moreover, it aims to help the quality assurance center in a higher education institution to apply its qualitys standards, and to make sure that they are being maintained and enhanced. This information system contains a core module and 17 sub-modules, which are described in this paper.

28 citations

Journal ArticleDOI
TL;DR: The aim of designing such a system is to provide an automation tool that avoids unnecessary and redundant tasks associated to quality in higher education institutions and helps all higher education stockholders to handle and monitor their tasks.
Abstract: Despite great efforts to assure quality in higher education institutions, the ambiguity of its related concepts and requirements constitute a big challenge when trying to implement it as an intelligent information system. The present work introduces a framework for an intelligent information system that manages the quality assurance in higher education's institutions. The aim of designing such a system is to provide an automation tool that avoids unnecessary and redundant tasks associated to quality in higher education institutions. In addition, the proposed system helps all higher education stockholders to handle and monitor their tasks. Moreover, it aims to help the quality assurance units in a higher education institution to apply their quality's standards and to make sure that they are being maintained and enhanced. This information system contains a core module and 18 sub-modules, which are described in detail. Finally, the characteristics and components of each of these sub-modules are also discussed.

23 citations