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International Research Journal on Advanced Science Hub最新文献

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Implementation of Disease Detection in Fruits using Neural Networks 利用神经网络实现水果病害检测
International Research Journal on Advanced Science Hub Pub Date : 2023-05-01 DOI: 10.47392/irjash.2023.s008
V. M, H. G, S. N, H. K, Sai Mounika K
{"title":"Implementation of Disease Detection in Fruits using Neural Networks","authors":"V. M, H. G, S. N, H. K, Sai Mounika K","doi":"10.47392/irjash.2023.s008","DOIUrl":"https://doi.org/10.47392/irjash.2023.s008","url":null,"abstract":"Commercialized agricultural operations are always looking for ways to reduce labour requirements without compromising output. Images of a few different fruit diseases, including Bitter Rot, and Sooty Blotch are employed in this method. Fruit infections’ ability to lower productivity and the global economy in the agricultural sector is a frustrating situation. In actuality, a healthy diet should be built around fruits. India has a population that is approximately 68 per cent dependent on agriculture. A significant percentage of the Indian economy is based on agriculture. Fruit cultivation has been a vital part of agriculture all over the world and has been the foundation of rural economies. Moni-toring a plant’s health and spotting illness manually is challenging. Agribusi-ness is a major contributor to the global economy, but its growth is slowing when compared to the rise in interest, and this ratio of interest to creation is expected to maintain high in the next few generations.","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132893216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Analysis of Supervised and Unsupervised Deep Learning Approaches for Identifying and Localizing Image Forgeries 图像伪造识别与定位的监督与非监督深度学习方法分析
International Research Journal on Advanced Science Hub Pub Date : 2023-05-01 DOI: 10.47392/irjash.2023.s003
K. S., P. Varma, Aravind J, Indra Gandhi K
{"title":"Analysis of Supervised and Unsupervised Deep Learning Approaches for Identifying and Localizing Image Forgeries","authors":"K. S., P. Varma, Aravind J, Indra Gandhi K","doi":"10.47392/irjash.2023.s003","DOIUrl":"https://doi.org/10.47392/irjash.2023.s003","url":null,"abstract":"The field of image forensics has become important in recent years as the use of digital images continues to grow. With the rise of sophisticated image editing software, it has become increasingly difficult to detect whether an image has been tampered with or not. Moreover, social media platforms have made the distribution of forged images to the general public a simple task. It is hence very important to develop automated methods that can detect such forgeries. In this study, we detect and localize splicing and copy-move image forgeries in images by using two different deep-learning techniques - Convolutional Neural Networks (CNN), which is a supervised approach and Self-Consistency Learning, an unsupervised approach. By comparing and contrasting the performance of these approaches, the research aims to gain a better understanding of how to effectively detect and locate image forgeries using deep learning. Ulti-mately, this research will contribute to the development of more reliable and accurate image forensic techniques, which will be of great benefit","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127325655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
An Efficient Regression Method To Predict Soil pH Using RGB Values 利用RGB值预测土壤pH值的有效回归方法
International Research Journal on Advanced Science Hub Pub Date : 2023-05-01 DOI: 10.47392/irjash.2023.s005
Mithun Shivakoti, S. K, A. Reddy
{"title":"An Efficient Regression Method To Predict Soil pH Using RGB Values","authors":"Mithun Shivakoti, S. K, A. Reddy","doi":"10.47392/irjash.2023.s005","DOIUrl":"https://doi.org/10.47392/irjash.2023.s005","url":null,"abstract":"The fertility of a soil is governed by potential of Hydrogen (pH) value of the soil. This research paper presents a novel approach for predicting the pH value of a soil by using RGB (Red, Green, Blue) values of an image. The study uti-lizes machine learning techniques to develop a model that can accurately predict the soil pH based on the colour information captured in an image of the soil. The model was trained with a dataset containing RGB and corresponding pH value as the attributes and tested using a variety of images. Results show that the proposed model is able to predict soil pH with minimal error, demonstrating the potential for using image analysis as a practical and efficient method for soil pH determination in agriculture and soil science. With the available dataset, various regression approaches have been implemented to predict the soil pH value, and eventually the experimental results shows that the polynomial regression is the most effective method as the data is not linear for analysing this dataset.","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125553002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Real time eye based Password Authentication by Eye Blinking System 基于眼睛眨眼系统的实时密码认证
International Research Journal on Advanced Science Hub Pub Date : 2023-05-01 DOI: 10.47392/irjash.2023.s001
Mr. Buddesab, N. Ashwin, Shruthi M, Rekha P, Pavan Mulgund
{"title":"Real time eye based Password Authentication by Eye Blinking System","authors":"Mr. Buddesab, N. Ashwin, Shruthi M, Rekha P, Pavan Mulgund","doi":"10.47392/irjash.2023.s001","DOIUrl":"https://doi.org/10.47392/irjash.2023.s001","url":null,"abstract":"The focus of this work is on PIN entering utilising the blinking approach, for user authentication and security, personal identification numbers are employed. PIN-based password verification users must input a physical PIN that can be cracked or hacked using shoulder surfing PIN entry process using eye blinks entering does not provide or easily leave any footprints behind, making it a more secure password entry option. Locating the blinks of an eye over creating picture frames in a consecutive order the Personal identification number is referred to as eye blinks-based authentication. This research shows how to resist shoulder surfing and thermal tracking attacks in real time. Today’s authentication technologies, such as passwords, fingerprint scanners, and PIN entry, are all based on one-time, static authentication mechanisms that are vulnerable to assaults. The Real-time","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127284950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Customer Segmentation in Tourism Industry using Machine Learning Models 基于机器学习模型的旅游业客户细分
International Research Journal on Advanced Science Hub Pub Date : 2023-05-01 DOI: 10.47392/irjash.2023.s006
Vikram S, G. Kumar, Vishwas T, Premsanth M, V. N
{"title":"Customer Segmentation in Tourism Industry using Machine Learning Models","authors":"Vikram S, G. Kumar, Vishwas T, Premsanth M, V. N","doi":"10.47392/irjash.2023.s006","DOIUrl":"https://doi.org/10.47392/irjash.2023.s006","url":null,"abstract":"Manual segmentation of customers consumes a lot of time, in some cases months, even years to break down information and track down patterns in it. Customer Segmentation done through machine learning models result in quick identification of the ideal customers. This research paper focuses on the tourism industry to target the right customers for their business. By using the tourism dataset of customers, the research paper aims to produce a better decision making visualization patterns through histogram, pie charts, and heatmaps. Moreover, the use of Bayesian Inference Model, Descriptive Basic Analysis and Linear Regression Analysis only on the important attributes makes the decision making for the tourism business quite easy. Finally, the use of clustering unsupervised machine learning models on the dataset generates the primary, secondary, and tertiary group of customers that the company can target for the sale of their tourism packages. Clustering models will generate clusters as the output where each cluster showcases a group of customers. The clustering models employed under this research are K-means, DBSCAN, Affinity Propagation, Mini Batch K-means and Optics Algorithm. The result showed that the Mini Batch K-means algorithm had a better accuracy score for the segmentation than other algorithms used","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"18 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114031694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Real-Time Computer Vision Based Hand Gesture Recognition 基于实时计算机视觉的手势识别
International Research Journal on Advanced Science Hub Pub Date : 2023-05-01 DOI: 10.47392/irjash.2023.s052
Rishav Nath Pati, Nagalakshmi Vallabhaneni, P. P, Yash Shekhawat, Srijan Paria
{"title":"Real-Time Computer Vision Based Hand Gesture Recognition","authors":"Rishav Nath Pati, Nagalakshmi Vallabhaneni, P. P, Yash Shekhawat, Srijan Paria","doi":"10.47392/irjash.2023.s052","DOIUrl":"https://doi.org/10.47392/irjash.2023.s052","url":null,"abstract":"The ability to recognize the shape and movement of hands can help improve the user experience in a wide range of technical domains and platforms. It can help you understand sign language and move your hands in the right way, for example. It can also make it possible for digital information and materials to be added on top of the real world in augmented reality. Here, I talk about a real-time, on-device hand gesture recognition solution that lets us control our system’s graphical user interface (GUI) with static and dynamic hand gestures that can be trained to do a set of actions that are similar to what we do with our","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125720622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Compound Facial Emotion Recognition based on Facial Action Coding System and SHAP Values 基于面部动作编码系统和SHAP值的复合面部情绪识别
International Research Journal on Advanced Science Hub Pub Date : 2023-05-01 DOI: 10.47392/irjash.2023.s004
Pooja Gupta, Srabanti Maji, Ritika Mehra
{"title":"Compound Facial Emotion Recognition based on Facial Action Coding System and SHAP Values","authors":"Pooja Gupta, Srabanti Maji, Ritika Mehra","doi":"10.47392/irjash.2023.s004","DOIUrl":"https://doi.org/10.47392/irjash.2023.s004","url":null,"abstract":"Human facial emotion recognition is a difficult task in computer-human inter-action. Facial emotion recognition is required in many applications like med-ical, security, video games, e-physiotherapy, and counselling. Literature has many studies that have focused only on 6 basic emotions but advanced studies suggest human emotions are not limited to these 6 basic emotions. A human face can exhibit many other emotions, which are generated by combining the two basic emotions, these derived emotions are known as compound emotions. Recognition of compound emotions is also a very important task; hence this study proposes the use of the Facial Action Coding System (FACS) to identify 12 compound emotions. The authors identified and derived the intensities of 17 AUs with Openface library. Finally, two machine learning classifiers SVM (Support Vector Machine) and KNN (K-nearest neighbour) were implemented to identify 12 compound emotions, and results were compared. The experimental results show that the SVM classifier outperformed with an emotion recognition rate of 98.31% while the recognition rate of K-NN was","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115804980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Internet of Things (IoT) Device Investigative Analysis Using Machine-to-Machine (M2M) Framework 使用机器对机器(M2M)框架的物联网(IoT)设备调查分析
International Research Journal on Advanced Science Hub Pub Date : 2023-05-01 DOI: 10.47392/irjash.2023.s007
Phaneendra Kanakamedala, Yarra Harika, Mamilla Krishnaveni, B. Nallani
{"title":"Internet of Things (IoT) Device Investigative Analysis Using Machine-to-Machine (M2M) Framework","authors":"Phaneendra Kanakamedala, Yarra Harika, Mamilla Krishnaveni, B. Nallani","doi":"10.47392/irjash.2023.s007","DOIUrl":"https://doi.org/10.47392/irjash.2023.s007","url":null,"abstract":"As we know that now a days the possibility of the uninterrupted attacks on the IOT devices are increasing. The less memory and the minute process-ing power of these appliances make it tough for the security analyst to store the records of the different attacks. The forensic analysis is used to evaluate the damage done on the devices due to numerous attacks. In this mecha-nism the attacks on the IOT devices are detects undoubtedly by using machine-to-machine (M2M) framework. In addition to the using machine-to-machine framework the machine learning algorithms also been used to identify various attacks automatically. Here we use the third-party logging server in order to issue. The execution will be studied in the form of accuracy, precision and the Random Forest gives the most accuracy.","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"313 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114413182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Tabib : Chatbot for Healthcare Automation with Audio Assistance using Artificial Intelligence Tabib:使用人工智能的语音辅助医疗保健自动化聊天机器人
International Research Journal on Advanced Science Hub Pub Date : 2023-05-01 DOI: 10.47392/irjash.2023.s002
Rekha P, Mr. Buddesab, Shruthi K, S. M., N. Ashwin
{"title":"Tabib : Chatbot for Healthcare Automation with Audio Assistance using Artificial Intelligence","authors":"Rekha P, Mr. Buddesab, Shruthi K, S. M., N. Ashwin","doi":"10.47392/irjash.2023.s002","DOIUrl":"https://doi.org/10.47392/irjash.2023.s002","url":null,"abstract":"Rekha P1, Buddesab 2, Shruthi K 3, Sathya M4, Nanda Ashwin 5 1Assistant Professor ,Department of ISE, MVJ Engineering college Bangalore-560067, Karnataka, India 2Associate Professor, Department of AIML, Cambridge Institute of Technology, Bangalore-560036, Karnataka, India 3Assistant Professor ,Department of CSE, The Oxford College Engineering Bangalore-560068, Karnataka, India 4Assistant Professor ,Department of CSE, The Oxford College Engineering Bangalore-560068, Karnataka, India 5Professor,Department of ISE, East Point college of Engineering and Technology, Bangalore-560049, Karnataka, India","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127810912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Personal Career Recommendation System 个人职业推荐系统
International Research Journal on Advanced Science Hub Pub Date : 2023-05-01 DOI: 10.47392/irjash.2023.s009
Chaganti Revanth, C. Yaswanth, Divya B, Sai Sumanth Reddy K, V. M
{"title":"Personal Career Recommendation System","authors":"Chaganti Revanth, C. Yaswanth, Divya B, Sai Sumanth Reddy K, V. M","doi":"10.47392/irjash.2023.s009","DOIUrl":"https://doi.org/10.47392/irjash.2023.s009","url":null,"abstract":"","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131053061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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