Advanced Journal of Graduate Research 2021-09-01T14:25:52+00:00 Adv. J. Grad. Research Open Journal Systems <p align="justify"><a title="Click for Journal homepage" href="" target="_blank" rel="noopener"><img style="float: right; padding-left: 15px; padding-right: 5px;" src="" alt="AJGR" /></a>Advanced Journal of Graduate Research is a multidisciplinary, international journal featuring the work of graduate students and young researchers. This journal seeks to disseminate the work of emerging students who focus on scientific/technical content, regardless of their academic discipline. <em>Adv. J. Grad. Res.</em> publishes research carried out by graduate students and young researchers (Bachelor's degree students and Master's degree students) that sound scientifically and technically valid. This journal will serve as a global platform to broadcast new research initiatives being carried out by today's brightest youths as part of their graduate project.<br />Advanced Journal of Graduate Research is published by AIJR publisher (India) and registered with CrossRef with doi: 10.21467/ajgr and ISSN of this journal is 2456-7108 [online].</p> Human Computer Interaction – Hand Gesture Recognition 2021-05-01T07:48:46+00:00 Riya Jain Muskan Jain Roopal Jain Suman Madan <p>The creation of intelligent and natural interfaces between users and computer systems has received a lot of attention. Several modes of knowledge like visual, audio, and pen can be used individually or in combination have been proposed in support of this endeavour. Human communication relies heavily on the use of gestures to communicate information. Gesture recognition is a subject of science and language innovation that focuses on numerically quantifying human gestures. It is possible for people to communicate properly with machines using gesture recognition without the use of any mechanical devices. Hand gestures are a form of nonverbal communication that can be applied to several fields, including deaf-mute communication, robot control, human–computer interaction (HCI), home automation, and medical applications. Many different methods have been used in hand gesture research papers, including those focused on instrumented sensor technology and computer vision. To put it another way, the hand sign may be categorized under a variety of headings, including stance and motion, dynamic and static, or a combination of the two. This paper provides an extensive study on hand gesture methods and explores their applications.</p> 2021-09-01T00:00:00+00:00 Copyright (c) 2021 Riya Jain, Muskan Jain, Roopal Jain, Suman Madan A Comparative Analysis of Expert Opinions on Artificial Intelligence: Evolution, Applications, and Its Future 2021-04-30T15:46:36+00:00 Falguni Saini Tanya Sharma Suman Madan <p>Artificial Intelligence (AI) is a field of computer science that primarily focuses on automating tasks that explicitly require human intelligence. The mechanics of AI technology majorly revolves around central affairs including knowledge representation, learning, problem-solving, reasoning, etc. Additionally, each discipline of AI focuses on a particular component to efficiently train the machines. Every branch of AI technology exploits knowledge in machines using diversified practices but with a clear idea of achieving the desired output. AI has evolved drastically over the past two decades and is considered the most in-demand technology at present times in varied fields including healthcare, education, forecasting, security, etc. This paper provides an extensive survey on artificial intelligence and related work going on in this field, how it differs from human intelligence, various subfields of AI and their importance, various issues related to AI and possible solutions along with and future trends related to this technology depicting people’s reliability on it and various possible concerns.</p> 2021-09-28T00:00:00+00:00 Copyright (c) 2021 Falguni Saini, Tanya Sharma, Suman Madan CNN Based Approach for Traffic Sign Recognition System 2021-05-26T13:35:27+00:00 Karan Singh Nikita Malik <p>Machine Learning (ML) involves making a machine able to learn and take decisions on real-life problems by working with an efficient set of algorithms. The generated ML models find application in different areas of research and management. One such field, automotive technology, employs ML enabled commercialized advanced driver assistance systems (ADAS) which include traffic sign recognition as a part. With the increasing demand for the intelligence of vehicles, and the advent of self-driving cars, it is extremely necessary to detect and recognize traffic signs automatically through computer technology. For this, neural networks can be applied for analyzing images of traffic signs for cognitive decision making by autonomous vehicles. Neural networks are the computing systems which act as a means of performing ML. In this work, a convolutional neural network (CNN) based ML model is built for recognition of traffic signs accurately for decision making, when installed in driverless vehicles.</p> 2021-09-26T00:00:00+00:00 Copyright (c) 2021 Karan Singh, Nikita Malik