2021 6th International Conference on Signal Processing, Computing and Control (ISPCC)最新文献_第10页

Classification of Heart Disease from MRI Images Using Convolutional Neural Network 利用卷积神经网络从MRI图像中分类心脏病

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609408

Ajay Sharma, R. Kumar, V. Jaiswal

引用次数: 0

Hyperspectral Image Classification using SVM with PCA 基于PCA的SVM高光谱图像分类

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609461

K. Mounika, K. Aravind, M. Yamini, P. Navyasri, S. Dash, V. Suryanarayana

引用次数: 8

Analysis Of Heart Risk Detection In Machine Learning Using Blockchain 使用区块链的机器学习中的心脏风险检测分析

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609353

R. Anand, S. Fazlul Kareem, R. Mohamed Arshad Mubeen, S. Ramesh, B. Vignesh

{"title":"Analysis Of Heart Risk Detection In Machine Learning Using Blockchain","authors":"R. Anand, S. Fazlul Kareem, R. Mohamed Arshad Mubeen, S. Ramesh, B. Vignesh","doi":"10.1109/ISPCC53510.2021.9609353","DOIUrl":"https://doi.org/10.1109/ISPCC53510.2021.9609353","url":null,"abstract":"Heart sickness is a main source for a lot of passings around the globe, and it is fundamental for each person to take great consideration of their heart. Cardiovascular infections (CVDs) turned into a significant reason for casualty in India. More than 54.5 million individuals experiencing CVDs in 2016 and one out of 4 passings are presently because of coronary illness. This task adds to conveying the expectation model for a coronary illness or respiratory failure utilizing AI and to make an easy to understand portable application that can get the information from the client’s savvy band or smartwatch for prompt forecasts. This tells individuals their coronary illness well and takes adequate measures to forestall heart absconds ahead of time. An alternate organic and actual boundaries like age, sex, pulse, circulatory strain, cholesterol level and chest torment locale can be utilized to estimate. The preparation and examination dataset, which comprises 14 distinct ascribes, was downloaded from kaggle.com. Managed calculations in AI will in general focus on information and the outcomes show that the proficiency of the proposed calculation method is contrasted and the high exactness with accuracy.","PeriodicalId":113266,"journal":{"name":"2021 6th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130498825","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

Security and privacy in IoT, Cloud and Augmented Reality 物联网、云和增强现实中的安全和隐私

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609520

Vidhyotma Gandhi, K. Ramkumar, Amanpreet Kaur, Payal Kaushal, J. Chahal, Jaiteg Singh

引用次数: 0

Effect of Random Mobility on the Performance of an Energy Efficient Fermat Point Based Geocast Routing Protocol for Wireless Adhoc and Sensor Networks 随机移动对无线自组网和传感器网络中基于费马点的高能效地球广播路由协议性能的影响

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609453

Kaushik Ghosh

引用次数: 1

Crime Scene Analysis Using Deep Learning 使用深度学习的犯罪现场分析

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609350

P. Mahesha, K. J. Royina, Sumi Lal, Y. Anoop Krishna, M. P. Thrupthi

{"title":"Crime Scene Analysis Using Deep Learning","authors":"P. Mahesha, K. J. Royina, Sumi Lal, Y. Anoop Krishna, M. P. Thrupthi","doi":"10.1109/ISPCC53510.2021.9609350","DOIUrl":"https://doi.org/10.1109/ISPCC53510.2021.9609350","url":null,"abstract":"Gathering evidence is one of the key activities during a criminal investigation. Image processing can assist in going over the scene of crime, or even recreating it. It isn’t always possible to expect the crime scene to be untampered with. However, with visual documentation of crime scenes comprising of various objects detected, it could be possible to come back to the images. This could assist in looking for something that has been discovered in further developments of the case. Additionally, with CCTV footage capturing tons of potentially crucial information, it is difficult for law enforcers themselves to go through the footage. Crime scene images are hard to find, and no known dataset is available to train the models directly on crime scene images. However, other popular datasets for image captioning do possess some crime scene images. The proposed approach is to train the models on a general vast dataset, MSCOCO. If the crime scene images are directly passed to the models, they will grab the main idea and give the sentence implying a person is dead. The idea is, however, to capture the more minute details ignoring the obvious conclusion that a person is dead. For crime scene images, the images are segmented into 9 images and passed individually to the model. This will generate 9 sentences for the input crime scene image with insight into the crime scene as opposed to captioning the crime scene. The three deep learning models proposed to use for generating sentences are: Inceptionv3-LSTM network, VGG-16-LSTM network and ResNet-50-LSTM network, and 0.1771, 0.11 and 0.1784 are the respective BLEU scores obtained. The users preferred the Inceptionv3-LSTM model over ResNet-50-LSTM model with a difference of 14.8% votes.","PeriodicalId":113266,"journal":{"name":"2021 6th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116021362","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: 3

Skin Pathology Detection Using Artificial Intelligence 基于人工智能的皮肤病理检测

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609516

Samardh Vadupu, Kalyana Srinivas Kandala, Anudeep Peddi, N. Yadav, G. Kumar, P. A. Harsha Vardhini

引用次数: 2

A Quantum Approach to Walk on Networks 网络行走的量子方法

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609345

Anurag Singh, Binshumesh Sachan

{"title":"A Quantum Approach to Walk on Networks","authors":"Anurag Singh, Binshumesh Sachan","doi":"10.1109/ISPCC53510.2021.9609345","DOIUrl":"https://doi.org/10.1109/ISPCC53510.2021.9609345","url":null,"abstract":"Some interesting findings can be achieved by modeling and visualizing networks which can include complex networks and large scale networks to name a few. These networks have been analyzed with the help of classical stochastic walks before. So, here in our proposed work, we provide the quantum version of the walk which basically involves making use of properties found in quantum computing. These properties can include such as quantum interference, no-cloning theorem, and restriction on intermediate measurement. In this proposed work, we present quantum circuit designs for discrete time random walk algorithms that operate on various networks.To demonstrate our ideas we have considered two different types of networks, the star network and an extended version of the star network.Though there exist a few research works related to quantum approach for random walk on networks, to the best of our knowledge, the ideas and approach we present here are unique. These ideas which we have discussed can be extended to more complex networks and systems as well. As an application of quantum walk we have shown, how results got after performing quantum walk can be used to identify critical nodes in such networks. Therefore, we have also provided some analysis of complex networks. Identification of critical nodes is important for robustness and survivability of the network.","PeriodicalId":113266,"journal":{"name":"2021 6th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123551748","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 Systematic Analysis of Applications Of Blockchain in Healthcare 区块链在医疗保健领域应用的系统分析

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609339

A. Agarwal, R. Tiwari, R. Kaushal, Naveen Kumar

引用次数: 16

Design and Development of Graphical User Interfaces for Detection of Forest Fires at early stages using Open-Source Technologies 使用开源技术设计和开发用于早期阶段森林火灾检测的图形用户界面

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609515

Jaskaran Singh, Chandan Taluja, Vijaya Choudhary, K. Chand, P. Guha

引用次数: 0