2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS)最新文献

{"title":"Emotion Recognition using Deep Stacked Autoencoder with Softmax Classifier","authors":"M. Mohana, P. Subashini","doi":"10.1109/ICAIS56108.2023.10073937","DOIUrl":"https://doi.org/10.1109/ICAIS56108.2023.10073937","url":null,"abstract":"Deep learning and computer vision research are still quite active in the field of facial emotion recognition (FER). It has been widely applied in several research areas but not limited to human-robot interaction, human psychology interaction detection, and learners’ emotion identification. In recent decades, facial expression recognition using deep learning has proven to be effective. This performance has been achieved by a good degree of self-learn kernels in the convolution layer which retains spatial information of images with higher accuracy. Even though, it often leads to convergence in non-optimal local minima due to randomized initialization of weights. This paper introduces a Deep stacked autoencoder in which the output of one autoencoder has given into the input of another autoencoder along with input values. A single autoencoder does not sufficient to extract the complex relationship in features. So, these concatenated features of the stacked autoencoder help to focus on highly active features during training and testing. In addition, this approach helps to solve inefficient data issues. Finally, trained autoencoders have fine-tuned with the Adam optimizer, and emotions are classified by a softmax layer. The outcomes of the proposed methodology on the JAFFE dataset are significant, according to experiments. The proposed method achieved 82% of accuracy, 85% of Precision, 82% of Recall, and 81% of F1-score. Additionally, the performance of the stacked autoencoder has been examined using the reconstruction loss and roc curve.","PeriodicalId":164345,"journal":{"name":"2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116561723","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}

{"title":"Deep Learning-based Hybrid Model for Severity Prediction of Leaf Smut Sugarcane Infection","authors":"V. Tanwar, Shweta Lamba, Bhanu Sharma","doi":"10.1109/ICAIS56108.2023.10073663","DOIUrl":"https://doi.org/10.1109/ICAIS56108.2023.10073663","url":null,"abstract":"Traditional models for predicting diseases in sugarcane crops show some drawbacks, including expensive costs for getting the data input needed to execute the model, a lack of spatial data, or a poor dataset. These problems are discussed in this work, which also develops a yield prediction fusion model. Convolutional neural networks (CNN) and support vector machines (SVM). make up the prediction model.In this work, the leaf smut infection of sugarcane is discussed. The sick plant is first photographed utilizing secondary sources. For feature extraction and classification of the various levels of severity of the smut infection, the best features of the deep learning techniques CNN and SVM are applied. Mild, Average, Severe, and Profound are the four seriousness prediction levels used in the study. Mendeley and Kaggle are the data repositories that were utilized, and the total size of the dataset was 950. The four severity level forecasts made by the suggested framework are 98% accurate.","PeriodicalId":164345,"journal":{"name":"2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS)","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116603898","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}

{"title":"Heuristics based Segmentation of Left Ventricle in Cardiac MR Images","authors":"Gowthamani R, Sasi Kala Rani K, R. M, A. S, D. B, ArunKumar L","doi":"10.1109/ICAIS56108.2023.10073912","DOIUrl":"https://doi.org/10.1109/ICAIS56108.2023.10073912","url":null,"abstract":"In the development of clinical decision supporting system, the clinical image classification and disease prognosis with human organ plays a main role in health care systems. Especially in cardiac Magnetic Resonance Imaging (MRI) diagnosing abnormal condition will be very difficult. Segmentation of left and right ventricles predicts heart problems and abnormalities and can be helpful to diagnose various heart issues. Cardiovascular disease plays a vital role in humans’ life. Diagnosis and prevention of left ventricular segmentation acts as an important part. Segmenting left ventricular is the complex and significant task to intensity and shape similarity with other organs in our body. In our proposed can be used to prevent cardiac disease effectively by automatically segmenting left ventricle with the help of MRI images, Improvised Convolution network and heuristic algorithm to detect the disease with high accuracy. The network is trained by considering the left ventricle’s comparatively small percentage of pixels in the overall image, . In the post- processing stage, the regions are determined based on their shapes and thresholding on the result image of the fully convolutional network. The performance is measured using the accuracy and loss observed as 96.79 percentage and 0.0029. The input image size was processed to 256 x 256 and the mask fitted the accuracy parameters at this size to the optimized rate of result.","PeriodicalId":164345,"journal":{"name":"2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS)","volume":"53 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113973908","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}

{"title":"Effective Location-based Recommendation Systems for Holiday using RBM Machine Learning Approach","authors":"R. Jayaraman, K. C, A. Sahaya Anselin nisha, K. Somasundaram, N. Naga Saranya, Vijendra Babu D","doi":"10.1109/ICAIS56108.2023.10073856","DOIUrl":"https://doi.org/10.1109/ICAIS56108.2023.10073856","url":null,"abstract":"Application developers and researchers took many steps in finding out proper tourism recommendations for various seasons. With the faster development in the travel department through modern technologies, it has gotten fundamental to present headways and upgrades in the administrations given to the sightseers, to ensure their ease of travel and satisfaction. Over the years, there has been no optimal system providing all the necessities required by a tourist. Based on the holidata recommendation, proposed system makes to decrease the time spent on the planning period and it helps to increase the deployment of process to be more effective. Regarding the customer preferences, the customer details and their location are shared and there are some other information available based on the users are, their destination trip, dates for the travel, budget and there are other user attractive aspects as it helps to have the effective trip. Based on the above things, the travel can be planned for the trip entirely. This system uses RBM to predict the user ratings and recommend the best attraction. An attempt has been made to reduce the MAE in RBM prediction.","PeriodicalId":164345,"journal":{"name":"2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS)","volume":"22 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114032004","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}

{"title":"IoT based Lithium-Ion Battery Monitoring System in Electric Vehicle","authors":"V. G, Aruna N, Janadharani S, Varshini N D","doi":"10.1109/ICAIS56108.2023.10073696","DOIUrl":"https://doi.org/10.1109/ICAIS56108.2023.10073696","url":null,"abstract":"A system to monitor and examine the parameters such as temperature, voltage, current, charge and discharge cycle of Lithium-ion battery is developed. Frequent monitoring and a way to manage the battery temperature is necessary to improve battery performance in electric vehicles. The performance characteristics of the batteries, being the vehicle’s primary power source determines the lifecycle, safety and mileage of an electric vehicle. The system consists of a microcontroller-based circuit, with solid state components for handling sensors, data communication module which is based on IOT protocol. The battery monitoring and management system is constructed with a liquid cooling system in which a coolant tube is inserted between battery cells to cool them when they are overheated. The system is installed in electric vehicles and by measuring above parameters it will help the users to optimally utilize battery and identify problems before any failure. Here the information of abnormality is sent to the user mobile phone through the IoT.","PeriodicalId":164345,"journal":{"name":"2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131267224","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}

{"title":"Network based Learning Platform Application Model for Enhancement of Realtime Working Systems","authors":"R. Shanmuga Priya, Sowbarnigaa Shanmugavadivel, Mehal Sakthi Muthusamy Sivaraja, M. Shifani Francis","doi":"10.1109/ICAIS56108.2023.10073739","DOIUrl":"https://doi.org/10.1109/ICAIS56108.2023.10073739","url":null,"abstract":"Learning platforms have become an integral part of the education system these days. Especially after the COVID era, education has become more allied with self-paced and remote learning and learning platforms have made it boom exponentially. Improper construction and implementation of such platforms can lead to huge risks for the users and the company. Data security is not taken much care of while building such platforms; instead, concentration is given to fancy front-end pages and attractive interfaces. This may not be good at all times. Data is one of the most powerful resources and can have a very big impact if misused. This paper proposes a networking-based approach to implementing such platform systems in a safe and organized way. Implementation using networking concepts gives a better hand in managing permissions, access rights, and security in all data-related transfers and communications. In terms of online gaming and real-time video communication, User Datagram Protocol (UDP) is often used because it is faster than Transmission Control Protocol (TCP) and is well-suited for real-time applications that cannot tolerate delays. UDP is a connectionless protocol, which means it doesn't retransmit lost data and therefore has lower overhead, making it a good choice for real-time applications like video conferencing and online gaming. Examples of such applications include Skype, Google Meet, Zoom, and Facetime. Based on these existing applications, this work introduces UDP in the field of Learning Platform Applications and builds a model on top of which real-time applications can be constructed. The proposed system makes use of UDP for all its requests, responses, and file transfers. The protocol itself is not very reliable, but the addition of provisions for acknowledgements in all requests and responses makes this system overcome transfer uncertainty. Implementation using networking concepts improves the speed, security, privacy, and customization abilities of the proposed system.","PeriodicalId":164345,"journal":{"name":"2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131432977","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}

{"title":"Data Mining in Education: A Review of Current Practices","authors":"Sai Sujith Mangalapalli, Sai Venkata Pavan Kumar Munnangi, Mallikharjuna Abhiram Mulpuri, Sahithi Snigdha Reddy Goguladinne, Subrahmanyam Kodukula, Satish Thatavarthi","doi":"10.1109/ICAIS56108.2023.10073932","DOIUrl":"https://doi.org/10.1109/ICAIS56108.2023.10073932","url":null,"abstract":"A significant amount of data is physically kept on hard drives or virtually stored in the cloud in the real world. Data is retained for a variety of purposes, such as learning, accessing, understanding, and so forth. Large amounts of data must be stored using an excellent infrastructure, which is quite expensive. Data mining tools were made available to help with this issue. Numerous industries, including healthcare, education, business, forensics, and law enforcement, use data mining techniques. This article surveys the significance of data mining techniques in the context of education. In addition to, the concurrent approaches are examined..","PeriodicalId":164345,"journal":{"name":"2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131482628","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}

{"title":"Realization of Halcon Image Segmentation Algorithm in Machine Vision for Complex Scenarios","authors":"L. Ke","doi":"10.1109/ICAIS56108.2023.10073925","DOIUrl":"https://doi.org/10.1109/ICAIS56108.2023.10073925","url":null,"abstract":"In the complex real world, with the application and popularization of the intelligent systems and information platforms, complex image recognition and segmentation need to be paid attention to. Therefore, this paper studies the realization of Halcon image segmentation algorithm in machine vision for complex scenarios. Firstly, the image complexity is analyzed. The core reason for firstly analyzing the image complex modelling is that for different images with the segmentation task, the training sets are different. Through the classification of the image complexity, different training and experimental sets can be targeted for performing the real-time tasks, and then, a novel complexity level model is defined. Then, a 2-step segmentation algorithm is proposed. For the simple and complex images, the segmentation models are different to make the comprehensive model efficient. For the complex image, the Selection of Cluster Number algorithm is applied. The proposed experiment compares the proposed model with the FCM, KFCM and SVM and the results have shown that the designed model is efficient considering different factors.","PeriodicalId":164345,"journal":{"name":"2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128044758","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}

{"title":"3D Game Design Aided by Multi-Dimensional Collision Detection Algorithm with GPU Optimization","authors":"Zikai Wang, Dasheng Pan, Bo Di","doi":"10.1109/ICAIS56108.2023.10073717","DOIUrl":"https://doi.org/10.1109/ICAIS56108.2023.10073717","url":null,"abstract":"This paper addresses the problem of the 3D game design aided by multi-dimensional collision detection algorithm with GPU optimization. For the designed model, our task will be focused on the 3D game design, the GPU performance on the image computing and neural network computing will be essential, hence, the graph neural network algorithm is considered. This study firstly considers the GPU optimization with shared memory model. Shared memory can be used to design the memory access mode in order to realize the combination of the memory access which improves the efficiency. Then, this study considers the multi-dimensional collision detection algorithm design. In order to achieve the unique representation of matrix translation and also spatial points, this paper then adopts the homogeneous coordinate system in matrix transformation. That improves the traditional model. Furthermore, the 3D game design steps are clarified. Based on the experiment under different scenarios, the game design sample code, the GPU performance and algorithm performance are all tested.","PeriodicalId":164345,"journal":{"name":"2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132838778","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}

{"title":"Smart Design Module Optimization of Intelligent Instruments Considering Cloud Storage","authors":"Huijie Liu","doi":"10.1109/ICAIS56108.2023.10073880","DOIUrl":"https://doi.org/10.1109/ICAIS56108.2023.10073880","url":null,"abstract":"With the recent continuous development of the computer, digital communication and also control the digital communication and control technologies, there are many fieldbus instruments and devices based on embedded systems, the efficient and fast design will be essential. This article analyzes the smart design module optimization of the intelligent instruments by considering the cloud storage. The designed model has 2 focuses, namely, the efficient data storage and intelligent instruments design. For the data storage, the local+cloud scenario is considered, the developed solution supports the flexible collocation of the computing resources and the various storage resources through decoupling of computing resources and storage resources. For the instruments design, the HART protocol is the transitional protocol for the transition from general analog communication to the digital communication. And this is used for the design, it is found that the control system designed in this paper system is shorter than the traditional control system, effectively saving the control time of industrial automation instrumentation. Through the test, this study found that the designed control system is superior to the traditional control system in terms of reaction time, which means the designed idea is efficient.","PeriodicalId":164345,"journal":{"name":"2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134189180","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}