2022 6th International Conference on Computing Methodologies and Communication (ICCMC)最新文献_第3页

Implementing Multiclass Classification to find the Optimal Machine Learning Model for Forecasting Malicious URLs 实现多类分类，寻找预测恶意url的最佳机器学习模型

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9754005

R. J. Samuel Raj, S. Anantha Babu, Helen Josephine V L, Varalatchoumy M, C. Kathirvel

引用次数: 0

Research on the Application of UAV Oblique Photography Algorithm in the Protection of Traditional Village Cultural Heritage 无人机倾斜摄影算法在传统村落文化遗产保护中的应用研究

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753856

Wei Zhou

引用次数: 2

Apple Leaf Disease Detection using Deep Learning 利用深度学习技术检测苹果叶病

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753985

S. K., Vishnu Raja P, Rima P, Pranesh Kumar M, Preethees S

{"title":"Apple Leaf Disease Detection using Deep Learning","authors":"S. K., Vishnu Raja P, Rima P, Pranesh Kumar M, Preethees S","doi":"10.1109/ICCMC53470.2022.9753985","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753985","url":null,"abstract":"In general, agriculture plays a very important role in contributing to human life on earth. Agriculture acts as the major source of providing food and economic growth of a region and as known plants are affected by several kinds of diseases either by excessive use of chemicals or by bacteria, viruses and fungus. It is important to diagnose plant diseases rightly, since use of wrong chemicals to treat the disease may increase the resistance of the pathogens which affects the plants. Manual diagnosis of diseases that affects the leaves of a plant will delay the process of diagnosis and treatment. Deep Learning frameworks can be used in detection and classification of the diseases. Convolution Neural Network based (CNN) based models are used in detection of apple leaf diseases. VGG16 framework is a CNN based architecture widely used in many deep learning classifications and it is easy to implement. VGG16 is used here for diagnosis and classifying apple leaf diseases. For implementing the framework tools and modules like Kaggle Notebook, Tensorflow, and Keras used. The VGG16 model is applied to the apple leaf disease dataset collected from the Kaggle repository. The proposed model aims in reducing complexity in classifying apple leaf disease using deep learning. The proposed system shows the best validation accuracy of 93.3% on the apple leaf disease dataset. This method outperforms some existing state-of-the-art. The processing time for each image is at an average of 14s. Hence the system proposed can be used by farmers to simplify the apple leaf disease classification process and help in early diagnosis and treatment of the disease.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128189636","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: 6

Predictive Analysis in Academic: An Insight to Challenges and Techniques 学术预测分析:对挑战和技术的洞察

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753869

A. Bhagya, P. Sripriya

引用次数: 0

Intelligent Transportation Planning System Based on Urban Network Topology Modeling and Remote Sensing Data Analysis 基于城市网络拓扑建模和遥感数据分析的智能交通规划系统

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9754004

Xinghua Li

引用次数: 0

Digitalization and Centralization of Medical Information and Patient History in Bangladesh 孟加拉国医疗信息和患者历史的数字化和集中化

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753690

Mogharab Nasim, Shekh Abdullah- Al- Noman, Ahmed Ragib Hasan, A. Sattar

{"title":"Digitalization and Centralization of Medical Information and Patient History in Bangladesh","authors":"Mogharab Nasim, Shekh Abdullah- Al- Noman, Ahmed Ragib Hasan, A. Sattar","doi":"10.1109/ICCMC53470.2022.9753690","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753690","url":null,"abstract":"Some remote area samples are reviewed through both online response and physical survey, where the parameters and specific keywords constructed and novel updated data samples of the conducted survey regions are focused. Through the conducted survey and processed novel dataset, the percentage of dominant demographics common health issues, their treatment locations, their further treatment of doctor suggested treatment locations, the origination capabilities of physical medical documents, and many other parameters are concluded. This survey generated a decision where the larger demography expressed their recurring need to visit remote doctors and medical centers for treatment. Different sections of our survey report concluded that while visiting these remote medical centers, they have often failed to organize their medical history documents. These reports solidify the need for a digital patient history database and the centralization of this database for ease of access from any location or medical center, or doctor’s chamber. Our project has also shed some light on the software and technical architecture that could be the foundation of a centralized database for patients’ medical history.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134089755","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 Enhanced Intelligent Attendance Management System for Smart Campus 面向智能校园的增强型智能考勤管理系统

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753810

J. Akila Rosy, S. Juliet

引用次数: 1

Speech Emotion Recognition using Machine Learning 使用机器学习的语音情感识别

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753976

Kotikalapudi Vamsi Krishna, Navuluri Sainath, A. Posonia

引用次数: 0

Face Recognition System Using Image Enhancement With PCA and LDA 基于PCA和LDA的图像增强人脸识别系统

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753787

Sparsh, Rohit Aggarwal, Sourabh Bhardwaj, K. Sharma

引用次数: 2

Apple Growth Analysis Using Deep Learning Approach in Orchards 用深度学习方法分析果园中的苹果生长

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753744

Pruthviraj Konu, K. P., Prabu Mohandas, Veena Raj

{"title":"Apple Growth Analysis Using Deep Learning Approach in Orchards","authors":"Pruthviraj Konu, K. P., Prabu Mohandas, Veena Raj","doi":"10.1109/ICCMC53470.2022.9753744","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753744","url":null,"abstract":"Detection of apples in orchards during its growth can help in estimating the productivity, but detecting all the apples will be a challenging part as some apples might be very small and occluded by leaves and branches. Although deep learning-based image segmentation algorithms have shown successful outcomes in crop area delineation, this method is still unable to precisely segment the regions of every target apple with significant overlap. Region Proposal Networks like Faster R-CNN can be used for detection, but they are not efficient in producing better results when the apples are very small. Furthermore, these systems can only detect apples at a specific stage of development, but they can’t predict yield without first learning about the growth features of apples as they mature. In order to solve the above mentioned problems that are involved during apple detection in orchards, an enhanced version of the You Only Look Once(YOLO)-V3 model is proposed for recognising apples in different kinds of situations. The proposed model has shown an F1 score of 0.802 which is a significant improvement when compared to already existing detection models.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117317494","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