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Object segregation using R-CNN

Computer vision is the science of computers and pack-age systems that can also recognize how images and scenes are perceived. PC Vision consists of a variety of solutions that include image recognition, object recognition, image generation, super-resolution of images, and much more. widely used in facial recognition, vehicle recognition, pedestrian counting, network mapping, security systems, and autonomous cars, but here we have a tendency to specialize in completely different sensible objects, those with different kinds of fruits, buttons, coins, etc. In this project, we use extremely correct object recognition algorithms and methods like RCNN, FastRCNN, FasterRCNN, Mobilnet, and fast but extremely correct methods like SSD. If we understand frameworks by using dependencies like TensorFlow, OpenCV, etc., we can recognize every single object in the image through the realm object in a highlighted area and determine every single object and assign its label to the object. This also includes the precision of every technique used to distinguish between objects.

Published by: Nihal Kumar Singh, Aakash Singh, Ashish Prasad, S. Usha

Author: Nihal Kumar Singh

Paper ID: V7I4-1511

Paper Status: published

Published: August 9, 2021

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Research Paper

A SEARCH FOR THE SOURCE AND ORIGIN OF WHITE PEBBLES/SILICA PEBBLES FOUND AT LONAR CRATER, BULDHANA DISTRICT, MAHARASHTRA, INDIA.

White pebbles of Silica origin, found in large quantities at Lonar Crater has been reported, though the source and origin of these pebbles as well as big boulders and basaltic rocks appearing white in color is not yet understood still. Research papers on Lonar Crater has not reported the abundance of pebbles and boulders present in Lonar Crater affected area, so far river pebbles and Lonar Crater pebbles exhibits similar in characteristics, physically and in chemical compositions, but boulders of big size are not found in any other water body or wetland water body. It has been reported through this paper of such big boulders and concluding that Lonar pebbles and big size boulders are not Lonar Crater origin. They have been transported by human activity and natural calamity. Boulders and pebbles may not be the evidence of meteorite impacted at Lonar Crater. They are not related to meteorite impact or volcanic eruption. They are not formed from the impacts of meteorites or volcanic eruptions.

Published by: Harishchandra Bala Mali, Raju D. Jadhav

Author: Harishchandra Bala Mali

Paper ID: V7I4-1672

Paper Status: published

Published: August 9, 2021

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Research Paper

Prediction of the stock price using Machine Learning techniques

As people's interest in forecasting stock prices has been increased in recent years, research on stock price analysis using big data and artificial intelligence. In this paper, we performed sentimental analysis by this work by creating and analyzing a sentimental vocabulary using news items. We can get the positive index of news stories using the sentimental dictionary. We can get the positive index of news stories for each date using the emotive dictionary. We can get the positive index of news stories for each date using the emotive dictionary. We can confirm the utility and possibility of sentimental analysis in the stock market by examining the correlation value between the positive index value and the stock return value.

Published by: Apoorva Y.

Author: Apoorva Y.

Paper ID: V7I4-1686

Paper Status: published

Published: August 9, 2021

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Research Paper

Production, assay, and optimization of Chitinase enzyme produce by bacterial isolates from fish waste dumped soil

The effective chitinase enzyme reducing organisms were isolated from prawn shell dumped soil. The isolates were named as FS1 &FS2. The chitinase enzyme was produced only when the organisms was grown on medium containing the prawn shell powder. Optimizations of enzyme production (pH, temparture, substrate concentration) were carried out. In this study both FS1(46.7U/ml) FS2 (77.8U/ml) bacterial strain produced maximum chitinase at pH 7.0. maximum chitinase enzyme was obtained in 0.5% substrate concentration (140U/ml) in 96hrs by FS1 and in 0.8% in substrate concentration (93.3U/ml) in 72 hrs. This enzyme was highly used for antifungal activity.

Published by: K. Shameem Rani, S. Kulandaivel

Author: K. Shameem Rani

Paper ID: V7I4-1704

Paper Status: published

Published: August 9, 2021

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Research Paper

Social distancing monitoring system using computer vision and YOLOv3

In the fight against COVID-19, social separation has proven to be an extremely successful strategy for slowing the disease's transmission. People are being motivated to limit their interactions with one another to reduce the risk of the virus spreading through physical or close touch. In the past, AI/Deep Learning has shown promise in solving a variety of everyday problems. We shall see a full explanation of how we may utilize Python, Computer Vision, and Deep Learning to detect social distancing in public spaces and workplaces in this suggested system. By analyzing the real-time video streams from the camera, the social distancing detection tool can determine whether people have kept a safe distance from each other in public settings and the workplace. We can integrate this tool into their security video systems to check if people at work, in factories, and in stores are keeping a safe distance from one another.

Published by: Devanshi Gupta, Saumya Srivastava, Sonali P. Dash

Author: Devanshi Gupta

Paper ID: V7I4-1676

Paper Status: published

Published: August 9, 2021

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Research Paper

Fundamental Frequency estimation and analysis of speech signal

The fundamental frequency is a critical component in speech signal processing analysis. The fundamental frequency (fo) is the rate at which the vocal cords vibrate, and the fundamental frequency range for a person is 120 to 400 Hz. This basic frequency varies depending on the size and form of the vocal cords, and it might differ for males, females, and children. Different time domain and frequency domain pitch detection techniques are utilized. The time-domain methods include autocorrelation and AMDF (Average Magnitude Difference Function), whereas the frequency domain algorithm is Cepstrum. The fundamental frequency may be determined by pitch preprocessing and extraction.

Published by: Mahesh M. Kamble, Tejal S.Bandgar

Author: Mahesh M. Kamble

Paper ID: V7I4-1681

Paper Status: published

Published: August 9, 2021

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