2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)最新文献_第6页

Future Agriculture Farm Management Using Augmented Reality: A Study 基于增强现实的未来农业农场管理研究

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058665

S. T, N. B, Nagamani H. Shahapure, Nagashree S, S. S. Shashidhara

{"title":"Future Agriculture Farm Management Using Augmented Reality: A Study","authors":"S. T, N. B, Nagamani H. Shahapure, Nagashree S, S. S. Shashidhara","doi":"10.1109/CCIP57447.2022.10058665","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058665","url":null,"abstract":"Augmented reality is a live direct or indirect view of physical-word. ‘Augment’ by computer generated or extracted real word sensory. Augmented Reality supplement your word with digital object of any sort. It combines physical and virtual word. This is one of the immersive technologies that will change your lifestyle in the near future. AR technology has the positive opportunity and service to educate change. Agriculture has been an important source of food and has always been a very important aspect. Agriculture is highly labor-intensive and highly dependent on the knowledge of individual farmers, causing management problems. It can make a decisive input to the best possible operation management of AR. Improve farmers reality in insect research and pest control AR correction compared to orthodox techniques and teaching methods (circles, speeches, etc.). In the eyes of the overall public, agriculture has a tendency to be easier. This is just like the easy case of sowing and reaping seeds. Agriculture is absolutely the becoming a member of collectively of diverse sciences and is a completely complicated manufacturing system. The demanding situations dealing with in enterprise appear like exacerbated with the aid of using the extra of a well-skilled team of workers in at the upward thrust countries. It isn't unusual for uneducated humans to interact in agriculture the use of suspicious archaic techniques. Not surprisingly, they fail, which ends up in diverse demographic demanding situations for society.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"289 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123172763","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 on Role of Quantum Computing in Machine Learning 量子计算在机器学习中的作用分析

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058679

Binju Saju, Madhwaraj Kango Gopal, B. Nithya, V. Asha, Vikash Kumar

引用次数: 0

Identification of Harmful animal detection using Image Processing Technique 基于图像处理技术的有害动物识别检测

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058651

Amrutha H M, Naresh E, Prashanth Kambli, Dayananda P, Niranjanamurthy M

{"title":"Identification of Harmful animal detection using Image Processing Technique","authors":"Amrutha H M, Naresh E, Prashanth Kambli, Dayananda P, Niranjanamurthy M","doi":"10.1109/CCIP57447.2022.10058651","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058651","url":null,"abstract":"Death due to snakebite causes mostly among farmers as they spend much time in the field like paddy, wheat etc. Illiteracy is one of the causes of death due to snakebites, because of illiteracy farmers may believe in superstitions as a need to create awareness about the death due to snake bites can be treated with medicines. Since ancient time's death by harmful animal bite numbers in thousands because of natural environment detecting harmful animals through human senses is challenging, hence we are design algorithm to detect harmful animals conveniently. It can be used for animal biologist to search some endangered species of animals. The harmful animals are present in the garden and green field's estates like tea estate, coffee estate, and in agricultural field we have harmful animals may harm to the farmers, to avoid the effect of the farmers. So far, no automatic sorting method has been planned to differentiate. Five most shared deadly dangerous animals. Over this scheme, we will detect different parameters from dangerous animal images for automatic harmful animal organization studies. Different computer visual perception issues, such as tracking motion, detecting objects, estimating human position, identifying actions, etc., have benefited greatly from deep learning [3]. In the similar way with the help of Yolo algorithm, we can easily understand the animal detection.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114332089","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

Identification of Breast Cancer Using RESNET152 使用RESNET152鉴别乳腺癌

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058689

D. Deepika, A. Lakshmi

{"title":"Identification of Breast Cancer Using RESNET152","authors":"D. Deepika, A. Lakshmi","doi":"10.1109/CCIP57447.2022.10058689","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058689","url":null,"abstract":"Breast cancer may be a malignant sickness that may be life threatening as a result of cancer cells begin to grow out of management and becomes untreatable if not diagnosed at early stage. The planned analysis focuses on up accuracy by designation the tumor at earlier stages with improved prediction rate. The application of the Resnet152 deep learning model is presented in this study. within the detection of carcinoma exploitation diagnostic procedure information on Wisconsin Dataset that consists of around five 100000 pictures. This analysis work leads to improved detection of tumor with associate accuracy of 98.5% compared to previous models like VGGNet19 with take a look at accuracy of 96.24%, MobileNetV2 77.84%. The pretrained model Resnet152 is employed for easier implementation, achieving higher accuracy than the previous strategies. This paper uses transfer learning to use theResnet152 on to custom trained model with a binary classifier that offers the result as malignant or benign. The model takes roentgenogram pictures as its input. complexness is that the issue with diagnostic procedure pictures. To urge price out of those we have a tendency to use image process and extract options to help radiologists in tumor detection and additionally minimizing the dependence of medical specialist.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116750507","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

Machine Learning Based Predictive Analytics For Agriculture Inventory Management System 基于机器学习的农业库存管理系统预测分析

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058690

N. Kumar, Shreyas Bhaskar, S.P Srinidhi, D. Shashank, Srivatsa G Karanam

{"title":"Machine Learning Based Predictive Analytics For Agriculture Inventory Management System","authors":"N. Kumar, Shreyas Bhaskar, S.P Srinidhi, D. Shashank, Srivatsa G Karanam","doi":"10.1109/CCIP57447.2022.10058690","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058690","url":null,"abstract":"When the globe was hit by the vicious Covid 19 pandemic, multiple industries faced the virus's wrath and that included the agricultural warehouse industry. Consequently, many warehouses which had received large shipment stocks of agricultural products were never to be used again as it had reached its expiration date. This led to major losses for the agricultural warehouses as well as losses in crops for farmers and large scale agriculturists. The main objective of this paper is to build a model which utilises 3 heavy-weight algorithms (Seasonal Autoregressive Integrated Moving Average - SARIMA, Long short term memory - LSTM and Holt Winters) and predicts the agricultural needs of retailers and consumers based on previous data from different warehouses. Deploying this system will not help in the regulation of goods in warehouses but will also aid in maximizing the profits and minimizing the losses for warehouses. The algorithm with the least MAE(Mean Absolute Error) value will be considered for forecasting the sales of the aforementioned product.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122646890","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

An Intelligent IoT Accident Detection System For Emergency Medical Services 面向紧急医疗服务的智能物联网事故检测系统

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058635

Govardhan R, Jagadeesh V Ranagatti, Lakshminath S M, Linganand Sangamad, Nagaraja J

{"title":"An Intelligent IoT Accident Detection System For Emergency Medical Services","authors":"Govardhan R, Jagadeesh V Ranagatti, Lakshminath S M, Linganand Sangamad, Nagaraja J","doi":"10.1109/CCIP57447.2022.10058635","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058635","url":null,"abstract":"Road accidents in the country continue to be a leading cause of death, disabilities and hospitalization despite our commitment and efforts. Road accidents happen at unexpected moments and thus cannot be anticipated. Lives are lost as a result of the inability to provide medical assistance on time. A small delay in notifying the concerned authorities can result in delayed medical help, which in turn results in loss of life. Hence, there must be a proper system that notifies nearby health centers as soon as an accident is detected. We aim to develop such a system which has the potential to so many lives. The solution which is proposed in this paper involves collision sensors to detect when an accident occurs, and then immediately alerting the emergency center. When an automobile meets with an accident, the microcontroller detects the collision with the help of sensors and immediately sends a voice message to the emergency center. This message contains GPS coordinates and timestamp of the accident. A camera module, which captures images periodically immediately after the accident, will be placed in the automobile. These images captured are then sent to the emergency center. These can be used to assess the severity of the accident and decide the best course of action.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126484252","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

Institution Management System: Student Module 院校管理系统:学生模块

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058674

R. Srimathi, J. Naskath, B. A. Mathavan, T. Archana Pown, M. S. Rabiya

{"title":"Institution Management System: Student Module","authors":"R. Srimathi, J. Naskath, B. A. Mathavan, T. Archana Pown, M. S. Rabiya","doi":"10.1109/CCIP57447.2022.10058674","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058674","url":null,"abstract":"Student Information Report System provides an interface for maintaining student records, academic details, admission details, etc. The maj or goal of this system is to create a college portal that can assure an organization's seamless operation. Nowadays, an automated system is demanded in our daily lives, which expanded computers and applications. The educational infrastructures like colleges and other institutions need to operate their manual functions on a computer system. This Institution Management System (IMS) helps institutions like colleges and other small scale institutions to function the online management of their resources. This project deals with part of an institution of information of student details using placement training and events attended details, academic details and other non-academic details. Using this system, any institution can maintain computerized records without any redundancy of student information. That means no one needs to be distracted by the non-relevant information while reaching out for specific data. Its services customize the projects that align with a particular client's objectives, goals and requirements. Student module, one can manage all institution management works for student records like project works, publishing papers/journals moreover, student promotion, student record maintenance. Student information includes admission details, transfer details, promotion details, course details, internship details, project details, higher studies, etc. This system ultimately allows any institution for better management of student information.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126419297","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

Novel approach of Using Periocular and Iris Biometric Recognition in the Authentication of ITS 眼周和虹膜生物识别在ITS认证中的新方法

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058656

Manjula Gururaj Rao, Priyanka H, Sumathi Pawar, K. K. Reddy, Usha Divakarla

{"title":"Novel approach of Using Periocular and Iris Biometric Recognition in the Authentication of ITS","authors":"Manjula Gururaj Rao, Priyanka H, Sumathi Pawar, K. K. Reddy, Usha Divakarla","doi":"10.1109/CCIP57447.2022.10058656","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058656","url":null,"abstract":"In a fast technology growing world with respect to the data, information security is the major criteria. To have the robust system the security is the foremost task. The personal identification system and biometrics are playing the important part in security of the system. To secure the system, the biometrics, OTP generation, irisdetection etc., are some of the securities concerned aspects are taken. Biometrics security system is one of the old security systems. During the biometric security systems, the main challenge is acquiring images with Visual Wavelength or Near-Infrared lighting in limited and unconstrained situations. This paper proposes a unique approach for personal authentication based on the merging of periocular and iris sensors. This approach may be used in the ITS (Intelligent Transport System). In the ITS, depending on the identification of the passengers, only privileged or the authorized passengers can be transported in the vehicle. The suggested system includes components for feature learning for categorization after image pre-processing. During image pre-processing, a slicedannular iris from an ocular image is turned into a remediedimage region. The local periocular region was extracted using iris localization parameters. Images suffer from varied noise abnormalities. Depending on the abnormality of the image, various data inadequacy and complicating situation arises. To deal with this problem, a novel data augmentation technique has been developed.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132387141","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

Mental State Evaluation with Machine Learning by utilizing Brain Signals 利用脑信号的机器学习心理状态评估

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058684

H. Mallikarjun

{"title":"Mental State Evaluation with Machine Learning by utilizing Brain Signals","authors":"H. Mallikarjun","doi":"10.1109/CCIP57447.2022.10058684","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058684","url":null,"abstract":"Mental State of the subject is evaluated by using EEG signals. EEG signal from the brain is taken by using Mind wave kit, which gives the raw EEG waves by the non-invasive method only using single electrode. To induce emotion in to the subject different emotional videos are shown and respective emotion EEGs are collected. so the electrical different EEG wave Alpha, Beta, Delta, Gama and theta varies, different waves having its nativity according to the emotional changes. Lucid scribe toolkit support to collection of data from the Mobile mind wave, the data exported to the excel and by finding the minimum and maximum value of every EEG wave, this is in the numerical values with known Mental states are set with numerical values like 0 neutral, 1 Happy, 2 Disgust, 3 Sad, 4 Angry. In this work Mental state evaluation using signal processing is carried by preparing 280 datasets are prepared by showing them different videos related to respective emotions. By using neuro sky's Mindwave kit brain waves are recorded at the forehead values are tabulated accordingly. 280 datasets are fed into Orange, open-source machine learning and data visualization module and algorithms are compared by extracting confusion matrices.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"47 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123267523","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

Virtual Telemedicine System for Remote Health Monitoring of Patients 用于患者远程健康监测的虚拟远程医疗系统

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058637

A. P, Apeksha Prabhu, Dhathri V, M. Reddy

{"title":"Virtual Telemedicine System for Remote Health Monitoring of Patients","authors":"A. P, Apeksha Prabhu, Dhathri V, M. Reddy","doi":"10.1109/CCIP57447.2022.10058637","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058637","url":null,"abstract":"The Objective of the proposed work is to apply an Internet of Things-based real-time remote patient monitoring system. Healthcare technology is one of the most popular studies in recent years. people's lifespans have successfully extended with the development of healthcare facilities and technologies. However, people in rural areas still have difficulty in obtaining healthcare services due to the barrier of distance and lack of doctors. The present work provides one of the best solutions to overcome this issue. During the pandemic situation, mortality was observed due to a lack of doctors and infrastructure as the patient-to-doctor ratio was more. The proposed experiment helps to overcome these problems. The data collected from various sensors are sent to the cloud and prediction along with a diagnosis of the patient are implemented. Algorithms like Logistic Regression, Random Forest and Extreme Gradient Boosting are being compared to obtain maximum accuracy. The Random Forest model is providing good accuracy for the prediction of a patient's condition compared to other algorithms.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120890448","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