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Research Paper

Mulberry leaf disease detection using YOLO

Many states in India have taken up sericulture as an important agro-industry with good results. The mulberry leaf is the most important economic component in sericulture since the quality and quantity of the leaf have a direct impact on the cocoon bearing. Leaf disease diagnosis and classification in mulberry plants can be useful to framers and researchers to identify and classify diseases. It is an interesting technique that aids in managing the pathogens within the fields automatically and effectively at a minimal cost. Many mulberry diseases usually have symptoms on the leaf during the early stages of infections. These can be easily analyzed and classified using images. This paper proposes a model for implementing mulberry infection detection using Convolution Neural Networks (CNN) and You Look Only Once (YOLO). The proposed model identifies and classifies mulberry leaf diseases effectively. The image is divided into several grids before the image processing. The speed and accuracy of detection and classification are relatively high.

Published by: Monalika Padma Reddy, Deeksha A.

Author: Monalika Padma Reddy

Paper ID: V7I3-2039

Paper Status: published

Published: June 22, 2021

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Review Paper

A critical review of the role of media and communication in social development and addressing issues surrounding scheduled castes/tribes

The media and communication are important tools for the development of people, particularly the marginalised and oppressed segments of society. India's scheduled castes/tribes are such marginalised communities that bear the brunt of the caste system, which is to blame for their backward social and economic status. The situation is exacerbated by the fact that they live in one of the country's most backward and impoverished regions, where development is lacking. This study looks at the role of the media in the development of the Scheduled Caste/Tribe community in India. As professional growth and social status are the indicators of development so these parameters are studied here. The main goal is to understand the various types of media and communication used by Scheduled Caste/Tribe people for occupational needs, as well as which of them is most effective for the purpose. This study also seeks to determine how effective media is in eliminating caste-related discrimination. The study employs an exploratory research design, and it is possible to conclude that media and communication play an important role in professional and social development.

Published by: Huzefa Mandasaurwala

Author: Huzefa Mandasaurwala

Paper ID: V7I3-1984

Paper Status: published

Published: June 22, 2021

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Research Paper

Heart Disease Prediction using Machine Learning Techniques

Thus preventing Heart diseases has become more than necessary. Good data-driven systems for predicting heart diseases can improve the entire research and prevention process, making sure that more people can live healthy lives. This is where Machine Learning comes into play. Machine Learning helps in predicting the Heart diseases, and the predictions made are quite accurate. The project involved analysis of the heart disease patient dataset with proper data processing. Then, different models were trained and predictions are made with different algorithms KNN, Decision Tree, Random Forest, SVM, Logistic Regression, Adaboost, etc . Thus, this project presents a comparative study by analyzing the performance of different machine learning algorithms.

Published by: Hanumanth K., Pawan Sahu, Riya Gaur

Author: Hanumanth K.

Paper ID: V7I3-1971

Paper Status: published

Published: June 22, 2021

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Research Paper

Automatic vehicle plate reorganization and detection by image processing and datamining approach

Automatic Vehicle Plate Recognition (AVPR) is the extraction of vehicle license plate information from an image or sequence of images. From the past thirty years, AVPR is becoming the challenging and interesting area of research. AVPR systems include a wide range of applications. Numerous real-world applications such as electronic toll collection, automatic parking management, access control, radar-based speed-control, border control, criminal pursuit, traffic law enforcement, etc. have been benefited from it. A lot of commercial AVPR systems are available today and yet there are many challenges and issues in accurate recognition of license plates. In India, number plate standards are rarely practised. Licence plates recognition has many problems like unnecessary text, different font size and font type, blur, skew, environmental factors etc. The variations of the licence plate types or environments cause challenges in the recognition of number licence plates. The major objective of this thesis is to develop a robust, accurate and reliable automatic vehicle license plate recognition system. Our suggested approach is performed in three phases: In the first phase, the input image is pre-processed. Character regions are extracted in the second phase, and in the third phase, recognition of extracted characters is performed. The present work has been performed to recognize Indian licence plates

Published by: Rangrajan Chaurasiya, Dr. Rajat Joshi

Author: Rangrajan Chaurasiya

Paper ID: V7I3-2034

Paper Status: published

Published: June 22, 2021

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Research Paper

Energy Efficient Cluster base routing approach by GWO and Tabu search optimization with Cluster Topology in Wireless sensor Network

A wireless sensor network is a group of nodes that are connected to each other by wireless connection. These types of networks work on the dynamic topology of the network because the positions of nodes in the wireless network are changing continuously. f WSN is increasing rapidly and simultaneously this technology is facing various major challenges of energy constraints depending upon the limited lifetime of batteries as each of its node relies on energy demand for performing the basic operational activities which has become the major reason behind the failure in wireless sensor networks. One node interruption may result in shutting down the overall operation of the system. The nodal operation relies on active TLOde, idle, and sleeping TLOdes. In case of active TLOdes, energy is consumed while transmitting or receiving the data. In case of idle TLOde, the node consumes the energy same as consumed in active type node whereas in case of sleeping TLOde, the node gets shut down in order to save the energy. To build the life expectancy of WSN the usage of vitality in a productive way is a TLOst normal issue.

Published by: Amardeep Kour, Dr. Rajat Joshi

Author: Amardeep Kour

Paper ID: V7I3-2033

Paper Status: published

Published: June 22, 2021

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Research Paper

Detection of plant leaf disease using image segmentation and Convolution Neural network and machine learning approaches

Productivity in agriculture is a big concern. Disease is important in agriculture because it occurs naturally in plants. if good precaution is not taken, so these plants and quantity is diminished. h. As a primary goal of the new Proposed architecture, the use of disease and classifier features is needed to identify proper disease features. The primary aim of successful design is residual learning such that vital facets of firm learning are also improved. Non-linear discriminative learning at the base of a neural network experiments were run in the Village with the measurements of 11 different diseases was designed using the CNN features, which yielded an accuracy rate of 98% on the validation sets.

Published by: Tasleema Jan, Dr. Rajat Joshi

Author: Tasleema Jan

Paper ID: V7I3-2032

Paper Status: published

Published: June 22, 2021

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