International Journal of Trend in Scientific Research and Development

The aim of information retrieval systems is to retrieve relevant information according to the query provided. The queries are often vague and uncertain. Thus, to improve the system, we propose an Automatic Query Expansion technique, to expand the query by adding new terms to the user s initial query so as to minimize query mismatch and thereby improving retrieval performance. Most of the existing techniques for expanding queries do not take into account the degree of semantic relationship among words. In this paper, the query is expanded by exploring terms which are semantically similar to the initial query terms as well as considering the degree of relationship, that is, “fuzzy membership- between them. The terms which seemed most relevant are used in expanded query and improve the information retrieval process. The experiments conducted on the queries set show that the proposed Automatic query expansion approach gave a higher precision, recall, and F measure then non fuzzy edge weights. 

Tarun Goyal | Ms. Shalini Bhadola | Ms. Kirti Bhatia "Automatic Query Expansion Using Word Embedding Based on Fuzzy Graph Connectivity Measures" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, 

URL: https://www.ijtsrd.com/papers/ijtsrd45074.pdf 

Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/45074/automatic-query-expansion-using-word-embedding-based-on-fuzzy-graph-connectivity-measures/tarun-goyal

callforpapercommerce, ugcapprovedjournalsincommerce, commercejournal

Image classification is perhaps the most important part of digital image analysis. In this paper, we compare the most widely used model CNN Convolutional Neural Network , and MLP Multilayer Perceptron . We aim to show how both models differ and how both models approach towards the final goal, which is image classification. 

by Souvik Banerjee | Dr. A Rengarajan "Hand-Written Digit Classification" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, 

URL: https://www.ijtsrd.compapers/ijtsrd42444.pdf 

Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/42444/handwritten-digit-classification/souvik-banerjee

internationaljournalofmanagement, callforpapermanagement, managementjournal 

Technologys scope has evolved into one of the most powerful tools for human development in a variety of fields.AI and machine learning have become one of the most powerful tools for completing tasks quickly and accurately without the need for human intervention. This project demonstrates how deep machine learning can be used to create a caption or a sentence for a given picture. This can be used for visually impaired persons, as well as automobiles for self identification, and for various applications to verify quickly and easily. The Convolutional Neural Network CNN is used to describe the alphabet, and the Long Short Term Memory LSTM is used to organize the right meaningful sentences in this model. The flicker 8k and flicker 30k datasets were used to train this. 

by Sreejith S P | Vijayakumar A "Image Captioning Generator using Deep Machine Learning" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, 

URL: https://www.ijtsrd.compapers/ijtsrd42344.pdf 

Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/42344/image-captioning-generator-using-deep-machine-learning/sreejith-s-p

callforpaperbiologicalscience, biologicalsciencejournal

Sentiment Analysis of the Reviews is important to understand the positive or negative effect of some process using their reviews after the experience. In the study the sentiment analysis of the reviews of drugs given by the patients after the usage using the boosting algorithms in machine learning. The Dataset used, provides patient reviews on some specific drugs along with the conditions the patient is suffering from and a 10 star patient rating reflecting the patient satisfaction. Exploratory Data Analysis is carried out to get more insight and engineer features. Preprocessing is done to get the data ready. The sentiment of the review is given according to the rating of the drugs. To classify the reviews as positive or negative three Classification models are trained LightGBM, XGBoost, and CatBoost and the feature importance is plotted. The result shows that LGBM is the best performing Boosting algorithm with an accuracy of 88.89 . 

by Sumit Mishra "Drug Review Sentiment Analysis using Boosting Algorithms" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, 

URL: https://www.ijtsrd.compapers/ijtsrd42429.pdf 

Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/42429/drug-review-sentiment-analysis-using-boosting-algorithms/sumit-mishra

internationaljournalsinengineering, callforpaperengineering, ugcapprovedengineeringjournal 

We concentrate on the task of Fashion AI, which entails creating images that are multimodal in terms of semantics. Previous research has attempted to make use of several generators for particular classes, which limits its application to datasets that have a just a few classes available. Instead, I suggest a new Group Decrease Network GroupDNet , which takes advantage in the generator of group convolutions and gradually reduces the percentages of the groups decoders convolutions. As a result, GroupDNet has a lot of influence over converting natural images with semantic marks and can produce high quality outcomes that are feasible for containing a lot of groups. Experiments on a variety of difficult datasets show that GroupDNet outperforms other algorithms in task. 

by Ashish Jobson | Dr. Kamlraj R "Fashion AI" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, 

URL: https://www.ijtsrd.compapers/ijtsrd41256.pdf 

Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/41256/fashion-ai/ashish-jobson

internationaljournalsofcomputerscience, callforpapercomputerscience, ugcapprovedjournalsforcomputerscience 

Driver assistance technologies that relieve the drivers task, as well as intelligent autonomous vehicles, rely on traffic sign recognition. Normally the classification of traffic signs is a critical challenge for self driving cars. For the classification of traffic sign images, a Deep Network known as LeNet will be used in this study. There are forty three different categories of images in the dataset. There are two aspects to this structure Traffic sign identification and Traffic sign classification. ADASs are designed to perform a variety of tasks, including communications, detection of road markings, recognition of road signs, and detection of pedestrians. There are two aspects to this structure Traffic sign identification and Traffic sign classification. In the methodologies for detecting and recognizing traffic signals various techniques, such as colour segmentation and the RGB to HSI model area unit, were applied for traffic sign detection and recognition. Different elements contribute to recognition of HOG. 

by Arpit Seth | Vijayakumar A "A Traffic Sign Classifier Model using Sage Maker" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, 

URL: https://www.ijtsrd.compapers/ijtsrd42411.pdf 

Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/42411/a-traffic-sign-classifier-model-using-sage-maker/arpit-seth

callforpapercommerce, ugcapprovedjournalsincommerce, commercejournal

This model is proposed to Automatically detect the number plate of vehicles. It uses YOLO You Look Only Once algorithm in order to detect the license plate. It takes the image as an input and puts it through Neural Network , then gives the output with bounding boxes. The method proposed here have some benefits over the traditional methods of detection of object. Yolo is really fast and efficient to handle detection of objects and it detects objects at a high speed up to 155 frames per second. Importance of automatically detecting number plate is that there are many fraud activities happening around us, to eliminate this mainly and then, also to retrieve vehicle details later after detecting the number plate. It detects the number plate and then make recognition or identify the license plate from the source image, which is called as image processing. This also works for number plates of different regions, it can detect for both grayscale as well as colour images. Also images can be captured by webcam and license plate can be detected. Number plates maybe broken sometimes, this model detects for broken ones also. It is also practical because of the low computational cost. It also has high accuracy and real time performance. 

by Anagha Jayakumar TN | Dr. S. K Manju Bargavi "Detection of Number Plate using Yolo" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, 

URL: https://www.ijtsrd.compapers/ijtsrd41286.pdf 

Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/41286/detection-of-number-plate-using-yolo/anagha-jayakumar-tn

peerreviewedinternationaljournal, callforpaperinugcapprovedjournals, paperpublicationforstudent

This paper is to provide a high level understanding of Generative Adversarial Networks. This paper will be covering the working of GAN’s by explaining the background idea of the framework, types of GAN’s in the industry, it’s advantages and disadvantages, history of how GAN’s are developed and enhanced along the timeline and some applications where GAN’s outperforms themselves. 

by Atharva Chitnavis | Yogeshchandra Puranik "An Extensive Review on Generative Adversarial Networks (GAN’s)" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, 

URL: https://www.ijtsrd.compapers/ijtsrd42357.pdf 

Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/42357/an-extensive-review-on-generative-adversarial-networks-gan’s/atharva-chitnavis

internationaljournalsofcomputerscience, callforpapercomputerscience, ugcapprovedjournalsforcomputerscience 

We concentrate on the task of Fashion AI, which entails creating images that are multimodal in terms of semantics. Previous research has attempted to use several class specific generators, which limits its application to datasets with a limited number of classes. Instead, we suggest a new Group Decreasing Network GroupDNet , which takes advantage in the generator of group convolutions and gradually reduces the percentages of the groups decoders convolutions. As a result, GroupDNet has a lot of influence over converting semantic labels to natural images and can produce plausible high quality results for datasets with a lot of groups. Experiments on a variety of difficult datasets show that GroupDNet outperforms other algorithms in the SMIS mission. We also demonstrate that GroupDNet can perform a variety of interesting synthesis tasks. 

by Ashish Jobson | Dr. Kamalraj R "Fashion AI Literature" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, 

URL: https://www.ijtsrd.compapers/ijtsrd42378.pdf 

Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/42378/fashion-ai-literature/ashish-jobson

callforpaperpapersconference, highimpactfactor, manuscriptpublication

 The recent coronavirus disease COVID 19 is extending very speedily over the world for the sake of its very infectious nature and is announced nationwide by the world health organization WHO . The COVID 19 is a group of coronavirus that has caused panic all over the world. It enters people through the sneezing and coughing of the infected person and weakens the person and it then slowly infects the affected person’s lungs. In this study, we have classified the chest X Ray images like Covid 19 infected chest images or normal chest images. Classifying the chest X Ray images is hard and time consuming work for human beings. Hence, an automatic Covid 19 infected chest X Ray image or normal chest classification tool is very useful even for experience humans to classify a lot of chest X Ray images. For that, we have proposed a new machine learning technique to automatically classify the chest Covid 19 infected X Ray images or normal chest images. Hence, we have used a Machine learning ML model like Support Vector Machine SVM to classify Covid 19 infected chest images and normal chest images. For this work, at first, we have preprocessed the chest X Ray image. Then we have extracted the distinct features from the chest X Ray images. After that, these features have trained into Machine Learning ML algorithm and finally classify these images into the category. From the experiment, The Support Vector Machine SVM models achieving an accuracy of up to 93.1 . 

by Md. Abdul Matin | Abdur Rahman | S M Abdullah Al Shuaeb | Anwar Hossen "Automatic Covid-19 Infected Chest X-Ray Image Classification using Support Vector Machine" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, 

URL: https://www.ijtsrd.compapers/ijtsrd41283.pdf 

Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/41283/automatic-covid19-infected-chest-xray-image-classification-using-support-vector-machine/md-abdul-matin

internationaljournalofmanagement, callforpapermanagement, managementjournal 

Nowadays all people are using websites to make their tour plans and to book hotels. Instead of approaching traditional travel agents, websites provide round the clock service at no cost. This paper proposes the Tourism guide website using Artificial Intelligence concept Fuzzy Logic. The Artificial Intelligence based website is more user friendly and understands the requirements of customer and helps the customer to make apt decision for making tour plans and book hotels and eating nice foods in various places. This paper proposes Fuzzy Logic based decision making to learn the mentality of customers and provides useful personalized and customized suggestions for tourists. The proposed system provides virtual tour to help the tourist for choosing the perfect tourist destinations. The proposed online system also provides a detailed itinerary for tourist spot selected by the traveller. 

by Dr. E. J. Thomson Fredrik | P. C. Rithika Ranjith "Online Tour Booking using Fuzzy Decision Making Method" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, 

URL: https://www.ijtsrd.compapers/ijtsrd42568.pdf 

Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/42568/online-tour-booking-using-fuzzy-decision-making-method/dr-e-j-thomson-fredrik

internationaljournalsinengineering, callforpaperengineering, ugcapprovedengineeringjournal 

This paper aims to introduce, review and summarize the basic concepts of reinforcement learning. It will provide an introduction to reinforcement learning in machine learning while covering reinforcement learning workflow, types, methods and algorithms used in it. 

by Shreya Khare | Yogeshchandra Puranik "A Review on Introduction to Reinforcement Learning" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, 

URL: https://www.ijtsrd.compapers/ijtsrd42498.pdf 

Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/42498/a-review-on-introduction-to-reinforcement-learning/shreya-khare

openaccessjournalofengineering, engineeringjournal, paperpublicationforengineering

Facial expression plays a major role in every aspect of human life for communication. It has been a boon for the research in facial emotion with the systems that give rise to the terminology of human computer interaction in real life. Humans socially interact with each other via emotions. In this research paper, we have proposed an approach of building a system that recognizes facial emotion using a Convolutional Neural Network CNN which is one of the most popular Neural Network available. It is said to be a pattern recognition Neural Network. Convolutional Neural Network reduces the dimension for large resolution images and not losing the quality and giving a prediction output whats expected and capturing of the facial expressions even in odd angles makes it stand different from other models also i.e. it works well for non frontal images. But unfortunately, CNN based detector is computationally heavy and is a challenge for using CNN for a video as an input. We will implement a facial emotion recognition system using a Convolutional Neural Network using a dataset. Our system will predict the output based on the input given to it. This system can be useful for sentimental analysis, can be used for clinical practices, can be useful for getting a persons review on a certain product, and many more. 

by Raheena Bagwan | Sakshi Chintawar | Komal Dhapudkar | Alisha Balamwar | Prof. Sandeep Gore "Facial Emotion Recognition using Convolution Neural Network" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, 

URL: https://www.ijtsrd.com/papers/ijtsrd39972.pdf 

Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/39972/facial-emotion-recognition-using-convolution-neural-network/raheena-bagwan

callforpaperphysics, physicsjournal

Nowadays Stress has been a quite common ailment in people. We believe that when technology is used to build understanding, it can help humanity in creative and effective ways. That idea lives at the core of our paper in an easily accessible app to help users. The paper elaborates plan to develop a virtual assistant a.k.a. chatbot that would act as a therapist to the masses. We propose to use Machine Learning and NLP together with web front end technologies. As per availability of data, Experiments show that the proposed methods achieve high accuracy in patient action understanding, error identification and task recommendation. The proposed virtual PT system has the potential of enabling on demand virtual care and significantly reducing cost for both patients and health care providers. 

by Tanmay Pachpande | Dewang Solanki | Venkat. P. Patil "Virtual Therapist for Psychological Healthcare" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, 

URL: https://www.ijtsrd.com/papers/ijtsrd38614.pdf 

Paper Url: https://www.ijtsrd.com/computer-science/artificial-intelligence/38614/virtual-therapist-for-psychological-healthcare/tanmay-pachpande

peerreviewedjournals, reviewpapers, callforpaperhealthscience

This is the new era of technology development where all the things and work is done by the machines. The goal of Information Technology is to develop a device which is able to work like a human itself. For that Artificial Intelligence, Machine Learning and Deep Learning are going to be used. Machine Learning is a subpart of the Artificial Intelligent which helps a machine to learn by itself. To apply learning processes on machines it required deep knowledge of programming, mathematics and statistics. Now it is not a big problem, as the technology is changing day by day the new concept known as No Code ML and Auto Code Generation are introduced. This helps the users to create a model without doing any kind of coding. In this new technology everyone is able to create a model and use machine learning. There are several platforms which provide this kind of facilities. The models created on those platforms give good accuracy and desire outcomes as well.

by Hiteshkumar Babubhai Vora | Hardik Anilbhai Mirani | Vraj Bhatt "Traditional Machine Learning and No-Code Machine Learning with its Features and Application" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, 

URL: https://www.ijtsrd.com/papers/ijtsrd38287.pdf 

Paper Url: https://www.ijtsrd.com/computer-science/artificial-intelligence/38287/traditional-machine-learning-and-nocode-machine-learning-with-its-features-and-application/hiteshkumar-babubhai-vora

callforpapersocialscience, ugcapprovedjournalsforsocialscience, socialsciencejournal

This paper provides an algorithmic procedure to predict interpolants of subsampled images. Given a digital image, one can subsample it by forcing pixel values in the alternate columns and rows to zero. Thus, the size of the subsampled image is reduced to half of the size of the original image. This means 75 of the information in the original image is lost in the subsampled image. The question that arises here is whether it is possible to predict these lost pixel values, which are called interpolants so that the reconstructed image is in accordance with the original image. In this paper, two novel interpolant prediction techniques, which are reliable and computationally efficient, are discussed. They are i interpolant prediction using neighborhood pixel value averaging and ii interpolant prediction using extended morphological filtering. 

by T. Kishan Rao | E. G. Rajan | Dr. M Shankar Lingam "Prediction of Interpolants in Subsampled Radargram Slices" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1 , December 2020, 

URL: https://www.ijtsrd.com/papers/ijtsrd38207.pdf

Paper URL : https://www.ijtsrd.com/computer-science/artificial-intelligence/38207/prediction-of-interpolants-in-subsampled-radargram-slices/t-kishan-rao

callforpapermedicalscience, medicalsciencejournal, manuscriptsubmission