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Multi-layer high-precision image classification technology embedded in SE modules 嵌入SE模块的多层高精度图像分类技术
International Journal of Advances in Computer Science and Technology Pub Date : 2022-08-10 DOI: 10.30534/ijacst/2022/011182022
{"title":"Multi-layer high-precision image classification technology embedded in SE modules","authors":"","doi":"10.30534/ijacst/2022/011182022","DOIUrl":"https://doi.org/10.30534/ijacst/2022/011182022","url":null,"abstract":"Due to the problems of model overfitting and gradient changes to reduce model performance in deep networks, the operation of improving the accuracy of image classification models by superimposing the number of layers of the network cannot be applied to all models. The Squeeze-and-Excitation (SE) module is a plug-and-play attention module in the field of computer vision that focuses on channel relationships. Experiments show that embedding SE modules in ResNet models of different scales brings much higher test accuracy improvement than increasing the depth of the original model; SE modules are extremely generalizable, and their embedding is universal to greatly improve the accuracy of different original models. Experimental results on the CIFAR-10 and Dogs-vs-Cats datasets show that the larger the amount of data, the more it can avoid the overfitting phenomenon of the model. A comparison experiment with the GoogLeNet model showed SENet being superior. According to the published research data, the application of SE modules accounts for 57.59% of the top 30 disciplines such as medical health, automation technology, telecommunications technology, electric power, light industry, automobiles, and transportation","PeriodicalId":294118,"journal":{"name":"International Journal of Advances in Computer Science and Technology","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130277982","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
Decision making Assessment model for University admission 大学录取决策评估模型
International Journal of Advances in Computer Science and Technology Pub Date : 2022-07-12 DOI: 10.30534/ijacst/2022/011172022
{"title":"Decision making Assessment model for University admission","authors":"","doi":"10.30534/ijacst/2022/011172022","DOIUrl":"https://doi.org/10.30534/ijacst/2022/011172022","url":null,"abstract":"Educational data mining has the potential to enhance the decision making by providing services to academicians. The students are confused when they aspire to get admission in selected colleges. Depending upon the university ranking the students get admission based on certain parameters. This paper presents a decision making assessment model that relies on combination of Distillation of Data through Human Judgment and fuzzy inference systems (FISs) to accommodate imprecise data using fuzzy rules after applying data attribute reduction to overcome uncertainty and complexity in the assessment model. This model was implemented using Weka and Matlab software","PeriodicalId":294118,"journal":{"name":"International Journal of Advances in Computer Science and Technology","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124713128","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
Monitoring activity and detecting unexpected events in surveillance footage using Deep CNN 使用深度CNN监控活动和检测监控录像中的意外事件
International Journal of Advances in Computer Science and Technology Pub Date : 2022-05-08 DOI: 10.30534/ijacst/2022/011152022
{"title":"Monitoring activity and detecting unexpected events in surveillance footage using Deep CNN","authors":"","doi":"10.30534/ijacst/2022/011152022","DOIUrl":"https://doi.org/10.30534/ijacst/2022/011152022","url":null,"abstract":"Security is always a primary concern in any domain, because there is an increasing in crime rate and illegal activities. Computer vision learning places a premium on abnormal detection and monitoring, which has numerous applications for dealing with a wide range of issues. We are all aware that there is a high demand for safety protection, personal properties and security, in recent years, video surveillance in systems has become a major focus in people's lives, particularly in government agencies and businesses. The technique we are employing is anomaly detection, which aids in distinguishing various patterns and identifying unusual patterns in a short period of time; these patterns are referred to as outliers. Surveillance videos provide real-time output of unusual events. Anomaly detection in video surveillance entails breaking the process down into three layers: video labelers, image processing, and activity detection. As a result, it detects abnormalities in videos for video surveillance, providing an application by providing accurate results in real-time scenarios. In this proposed work, abnormal events are detected with 98.5 percent accuracy using images and videos. To prevent virus transmissions across the world the government forced to announce the lockdown due to COVID-19 pandemic. As a result, production at manufacturing plants in most areas was halted, resulting in the cessation of all economic activity. There is an even greater need to ensure the safety of youngsters. While there is a pressing need to revive workforce production. The work helps in maintaining social distance and wearing face masks while at work clearly reduces the risk of transmission. Monitor activity decided to identify violations using computer vision (Not Wearing Mask) Real-time alerts that send a trigger and an email with a photo of a rule violation to the appropriate authority as evidence of a rule violation","PeriodicalId":294118,"journal":{"name":"International Journal of Advances in Computer Science and Technology","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133424142","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 Exploration of Community Detection and Recommendation Systems (CDR) in Social Networks 社交网络中社区检测与推荐系统(CDR)的探索
International Journal of Advances in Computer Science and Technology Pub Date : 2021-10-06 DOI: 10.30534/ijacst/2021/0110102021
D. Gopal, Mantri Charan Babu, D. K. K. Kumar
{"title":"An Exploration of Community Detection and Recommendation Systems (CDR) in Social Networks","authors":"D. Gopal, Mantri Charan Babu, D. K. K. Kumar","doi":"10.30534/ijacst/2021/0110102021","DOIUrl":"https://doi.org/10.30534/ijacst/2021/0110102021","url":null,"abstract":"Community detection and Recommender systems are assumed as significant parts in helping the web users discover important information by proposing information of likely interest to them and a central task for network analysis means to segment a network into numerous substructures to assist with uncovering their inactive capacities. Community detection has been widely concentrated in and extensively applied to numerous real world network problems. Because of the possible worth of social relations in recommender systems, social recommendation has drawn in expanding consideration in recent years. As the issues that network strategies attempt to solve and the network information to be determined become progressively more complex, new methodologies have been proposed and created, traditional ways to deal with community detection and recommendation commonly use probabilistic graphical models and implement an assortment of earlier information to deduce community structures. Regardless of all the new progression, there is as yet an absence of astute comprehension of the hypothetical and methodological supporting of local area location, which will be fundamentally significant for future advancement of the space of social network analysis. In this paper, we start by giving conventional meanings of social networks terms and talk about the novel property of social networks and its implications. Unified architecture of network community finding methods to characterize the state-of-the-art of the field of community detection. In particular, we give a complete survey of the current community detection techniques and audit of existing recommender systems examine some exploration bearings to further develop social network capabilities.","PeriodicalId":294118,"journal":{"name":"International Journal of Advances in Computer Science and Technology","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134593311","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
A Conceptual Framework for Detecting and Analysing Website Performance Anomalies 一个检测和分析网站性能异常的概念框架
International Journal of Advances in Computer Science and Technology Pub Date : 2021-09-08 DOI: 10.30534/ijacst/2021/011092021
{"title":"A Conceptual Framework for Detecting and Analysing Website Performance Anomalies","authors":"","doi":"10.30534/ijacst/2021/011092021","DOIUrl":"https://doi.org/10.30534/ijacst/2021/011092021","url":null,"abstract":"Anomalies in website performance are very common. Most of the time they are short and only affect a small portion of the users. However, in e-commerce an anomaly is very expensive. Just one minute with an underperforming site means a big loss for a big e- commerce retailer. E-commerce web site operations are heavily transactional and prone to small, short time failures. Anomalies are sometimes small, and as such, they are not caught by the retailer web operations. However, the customers do perceive these anomalies. This paper highlights the major websites anomalies and formulates a conceptual framework that analyses them.","PeriodicalId":294118,"journal":{"name":"International Journal of Advances in Computer Science and Technology","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132595596","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
Fake News Detection System Using machine Learning 利用机器学习的假新闻检测系统
International Journal of Advances in Computer Science and Technology Pub Date : 2021-06-16 DOI: 10.30534/ijacst/2021/021062021
{"title":"Fake News Detection System Using machine Learning","authors":"","doi":"10.30534/ijacst/2021/021062021","DOIUrl":"https://doi.org/10.30534/ijacst/2021/021062021","url":null,"abstract":"Expansion of deluding data in ordinary access news sources, for example, web-based media channels, news web journals, and online papers have made it testing to distinguish reliable news sources, hence expanding the requirement for computational apparatusesready to give bits of knowledge into the unwavering quality of online substance. In this paper, every person center around the programmed ID of phony substance in the news stories. In the first place, all of us present a dataset for the undertaking of phony news identification. All and sundry depict the pre-preparing, highlight extraction, characterization and forecast measure in detail. We've utilized Logistic Regression language handling strategies to order counterfeit news. The prepreparing capacities play out certain tasks like tokenizing, stemming and exploratory information examination like reaction variable conveyance and information quality check (for example invalid or missing qualities). Straightforward pack of-words, n-grams, TF-IDF is utilized as highlight extraction strategies. Strategic relapse model is utilized as classifier for counterfeit news identification with likelihood of truth.","PeriodicalId":294118,"journal":{"name":"International Journal of Advances in Computer Science and Technology","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133337401","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
Digital Wellness: A Smart Health Care System Using Machine Learning 数字健康:使用机器学习的智能医疗保健系统
International Journal of Advances in Computer Science and Technology Pub Date : 2021-06-15 DOI: 10.30534/ijacst/2021/011062021
{"title":"Digital Wellness: A Smart Health Care System Using Machine Learning","authors":"","doi":"10.30534/ijacst/2021/011062021","DOIUrl":"https://doi.org/10.30534/ijacst/2021/011062021","url":null,"abstract":"Nowadays,people face various diseases due to environmental condition and their living habits. So the prediction of disease at an earlier stage becomes an important task. But the accurate prediction based on symptoms becomes too difficult for the doctor. The correctprediction of disease is the most challenging task. To overcome this problem data mining plays an important role to predict the disease. Medical science has a large amount of data growth per year. Due to the increasing amount of data growth in the medicaland healthcare field the accurate analysis of medical data has been benefits from early patient care. With the help of disease data, data mining finds hidden pattern information in a huge amount of medical data. We proposed general disease prediction based on the symptoms of the patient. For the disease prediction, we use Convolutional neural network (CNN) machine learning algorithm for the accurate prediction of disease. For disease prediction required disease symptoms dataset. After general disease prediction, this system able to gives the risk associated with a general disease which is a lower risk of general disease or highe","PeriodicalId":294118,"journal":{"name":"International Journal of Advances in Computer Science and Technology","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134417856","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
Deep Learning based Pneumonia detection using X-Ray 基于深度学习的x射线肺炎检测
International Journal of Advances in Computer Science and Technology Pub Date : 2020-06-25 DOI: 10.30534/ijacst/2020/06962020
Asaph M Joyer George
{"title":"Deep Learning based Pneumonia detection using X-Ray","authors":"Asaph M Joyer George","doi":"10.30534/ijacst/2020/06962020","DOIUrl":"https://doi.org/10.30534/ijacst/2020/06962020","url":null,"abstract":"Pneumonia has been one of the diseases that affect the lungs and within a short period of time, due to the accumulation of fluid in lungs patients may experience shortage of breath resulting in death. So the early diagnosis is important for helping the patients. This paper focuses on the detection of pneumonia by x-ray imaging and using a model trained by using convolutional neural networks. In this paper the deep learning architecture for the classification task, which is trained with modified images, through multiple steps of preprocessing? Our classification method uses convolutional neural networks for classifying the images. The trained model yields an accuracy of 96%.","PeriodicalId":294118,"journal":{"name":"International Journal of Advances in Computer Science and Technology","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121199247","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
User Authentication for Smart Home using IoT Devices 使用物联网设备的智能家居用户认证
International Journal of Advances in Computer Science and Technology Pub Date : 2020-06-25 DOI: 10.30534/ijacst/2020/04962020
A. John
{"title":"User Authentication for Smart Home using IoT Devices","authors":"A. John","doi":"10.30534/ijacst/2020/04962020","DOIUrl":"https://doi.org/10.30534/ijacst/2020/04962020","url":null,"abstract":"A smart home is one that provides its home owners comfort, security, energy, efficiency and convenience at all times, regardless of whether anyone is home. End-user devices, such as mobile phones and tablets, have become essential tools for accessing smart homes. Although mobile phones are equipped with different means of authentication such as fingerprint readers, face lock, etc., these methods are only employed at time of access. User Authentication for Smart Home Networks Based on the Usage of IoT Device. It presents a continuous user authentication model based on behavioral features extracted from user interactions with IoT devices. If and when an unauthorized access occurs, permission to access the system would be denied. Consecutively an alert message would be sent to the emergency phone number provided during time of user registration.","PeriodicalId":294118,"journal":{"name":"International Journal of Advances in Computer Science and Technology","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121610225","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
Android Controlled Smart Wheelchair with Gesture and Voice Control 安卓控制的智能轮椅与手势和语音控制
International Journal of Advances in Computer Science and Technology Pub Date : 2020-06-25 DOI: 10.30534/ijacst/2020/07962020
Sreeraj, M R
{"title":"Android Controlled Smart Wheelchair with Gesture and Voice Control","authors":"Sreeraj, M R","doi":"10.30534/ijacst/2020/07962020","DOIUrl":"https://doi.org/10.30534/ijacst/2020/07962020","url":null,"abstract":"Being disabled brings about a feeling of isolation from the outside world and a sense of dependability as we have to depend on others help for just moving from one place to other and many other basic needs. [1] Wheelchair has solved this problem to an extent as it’s provides personal mobility for the aged and disabled. [1] [2] But it is very difficult for the disabled people to use the manual power of the wheelchair independently. As a solution to this problem, we have put forward a power wheelchair which can be controlled with a simple android device using IOT technology.[2] We have used the technology initially used to control robots to control a power wheelchair using an android device either by touch joysticks or by voice commands or by gesture.[1][5]","PeriodicalId":294118,"journal":{"name":"International Journal of Advances in Computer Science and Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123308614","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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