2021 6th International Conference on Signal Processing, Computing and Control (ISPCC)最新文献_第9页

Deep Learning to Detect Plant Diseases 深度学习检测植物病害

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609389

Rajiv Kumar

{"title":"Deep Learning to Detect Plant Diseases","authors":"Rajiv Kumar","doi":"10.1109/ISPCC53510.2021.9609389","DOIUrl":"https://doi.org/10.1109/ISPCC53510.2021.9609389","url":null,"abstract":"Economy of any nation shares a major part with the agriculture and crop production. Good yield is badly impacted by the diseases in plants and crops. Due to involvement of manual inspection on majority, poses a challenge to identify the plant diseases and in turn the crop yield is reduced, or quality is affected. Monitoring plants and crops spread over a large area is tedious task for the farmers or cultivators. Sometimes, the disease may not be known to the farmer. The present paper presents a system involving a standard smartphone to predict the plant diseases using machine learning approach. The proposed system collects data, as plant disease images, and that dataset is used to detect various diseases of plants and crop. It potentially benefits the cultivators as it is capable to detect the diseases without minimal human intervention with prompt results. Further, the proposed technique helps in detecting diseases during its early stage to safeguard the yield. Neural network-based model is trained to detect plant diseases and the crop types. During test results, the model achieves an accuracy of 96.78% in detecting diseases which is of significant use to the cultivators. Further, the system recommends the possible pesticides to use in every category of the disease.","PeriodicalId":113266,"journal":{"name":"2021 6th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"76 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114036703","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 Efficient Temporal Feature Aggregation of Audio-Video Signals for Human Emotion Recognition 一种用于人类情感识别的音频-视频信号的有效时间特征聚合

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609528

Lovejit Singh, Sarbjeet Singh, N. Aggarwal, Ranjit Singh, Gagan Singla

{"title":"An Efficient Temporal Feature Aggregation of Audio-Video Signals for Human Emotion Recognition","authors":"Lovejit Singh, Sarbjeet Singh, N. Aggarwal, Ranjit Singh, Gagan Singla","doi":"10.1109/ISPCC53510.2021.9609528","DOIUrl":"https://doi.org/10.1109/ISPCC53510.2021.9609528","url":null,"abstract":"Due to the significance of human behavioral intelligence in computing devices, this work focused on the facial expressions and speech of humans for their emotion recognition in multimodal (audio-video) signals. The audio-video signals consist of frames to represent the temporal activities of facial expressions and speech of humans. It become challenging to determine the efficient method to construct a spatial and temporal feature vector from the frame-wise spatial feature descriptor to describe the facial expressions and speech temporal information in audio-video signals. In this paper, an efficient temporal feature aggregation method is presented for human emotion recognition in audio-video signals. The Local Binary Pattern (LBP) feature of facial expressions and Mel Frequency Cepstral Coefficients (MFCCs) and its $Delta+DeltaDelta$ of speech are computed from each frame. The experiment analysis is performed to decide the efficient method for temporal feature aggregation, i.e., sum normalization or statistical functions, to construct a spatial and temporal feature vector. The multiclass Support Vector Machine (SVM) classification model is trained and tested to evaluate the performance of temporal feature aggregation method with LBP features and MFCCs and its $Delta+DeltaDelta$ features. The Bayesian optimization (BO) method determines the optimal hyper-parameters of the multiclass SVM classifier for emotion detection. The experiment analysis of proposed work is performed on publicly accessible and challenging Crowd-sourced Emotional Multimodal Actors-Dataset (CREMA-D) and compared with existing work.","PeriodicalId":113266,"journal":{"name":"2021 6th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"25 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":"114873680","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

Design and Comparative analysis of Mux Tree using Different Low Power Design Techniques 采用不同低功耗设计技术的复用树设计与比较分析

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609494

Kanika Sharma, Ashwni Kumar

引用次数: 0

A Comprehensive Review on Clustering in WSN: Optimization Techniques and Future Research Challenges 无线传感器网络聚类研究综述:优化技术与未来研究挑战

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609420

Abha Sharma, Prasenjit Das, R. B. Patel

引用次数: 2

Encryption Algorithms based on Security in IoT (Internet of Things) 物联网中基于安全的加密算法

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609495

Amanpreet Kaur, Gurpreet Singh

{"title":"Encryption Algorithms based on Security in IoT (Internet of Things)","authors":"Amanpreet Kaur, Gurpreet Singh","doi":"10.1109/ISPCC53510.2021.9609495","DOIUrl":"https://doi.org/10.1109/ISPCC53510.2021.9609495","url":null,"abstract":"The Internet is evolving everywhere and expanding its entity globally. The IoT(Internet of things) is a new and interesting concept introduced in this world of internet. Generally it is interconnected computing device which can be embedded in our daily routine objects through which we can send and receive data. It is beyond connecting computers and laptops only although it can connect billion of devices. It can be described as reliable method of communication that also make use of other technologies like wireless sensor, QR code etc. IoT (Internet of Things) is making everything smart with use of technology like smart homes, smart cities, smart watches. In this chapter, we will study the security algorithms in IoT (Internet of Things) which can be achieved with encryption process. In the world of IoT, data is more vulnerable to threats. So as to protect data integrity, data confidentiality, we have Light weight Encryption Algorithms like symmetric key cryptography and public key cryptography for secure IoT (Internet of Things) named as Secure IoT. Because it is not convenient to use full encryption algorithms that require large memory size, large program code and larger execution time. Light weight algorithms meet all resource constraints of small memory size, less execution time and efficiency. The algorithms can be measured in terms of key size, no of blocks and algorithm structure, chip size and energy consumption. Light Weight Techniques provides security to smart object networks and also provides efficiency. In Symmetric Key Cryptography, two parties can have identical keys but has some practical difficulty. Public Key Cryptography uses both private and public key which are related to each other. Public key is known to everyone while private key is kept secret. Public Key cryptography method is based on mathematical problems. So, to implement this method, one should have a great expertise.","PeriodicalId":113266,"journal":{"name":"2021 6th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"5 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":"116407517","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

Performance Analysis of TCP Queues: Effect of Buffer Size and Round Trip Time TCP队列的性能分析:缓冲区大小和往返时间的影响

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609523

Lokesh Bommisetty

{"title":"Performance Analysis of TCP Queues: Effect of Buffer Size and Round Trip Time","authors":"Lokesh Bommisetty","doi":"10.1109/ISPCC53510.2021.9609523","DOIUrl":"https://doi.org/10.1109/ISPCC53510.2021.9609523","url":null,"abstract":"In this paper, we demonstrate the effect of buffer size and the round trip time (RTT) on the statistical, dynamical properties of the transport control protocol (TCP) flows. We analyze the queue metrics like link utilization, queue size and packets lost with respect to buffer sizes and RTT. To analyze the network performance, we consider three buffer regimes: large buffer, intermediate buffer, and small buffer. In large buffer regime, we consider the delay bandwidth product gives that buffer size. The intermediate buffer size is determined by scaling the size of large buffer with the square root of the TCP flows using that link. In small buffer regime, fixed length buffer is considered. We study the aggregate traffic flow behaviour of multiple TCP flows and the compound TCP models of traffic flows. The behaviour of fluid models of traffic flows is studied to analyze the dependency of stability, goodput and the magnitude of oscillations when the model is unstable. We perform the packet level simulations of single bottleneck and two bottle neck queues to study the performance parameters like queue size, dropped packets and link utilisation for different buffer sizes and RTTs. We suggest that the buffer sizes can be much smaller than the buffer sizes recommended currently with the support of statistical and control theoretical analysis.","PeriodicalId":113266,"journal":{"name":"2021 6th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"34 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":"126358066","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

Role of Data Analysis in Higher Education 数据分析在高等教育中的作用

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609509

Sidharth Gautam

引用次数: 0

Security Challenges and Issues in IoT 物联网中的安全挑战和问题

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609486

Sanjeev Kumar, Sukhvinder Singh Deora

引用次数: 1

Wireless Communication Technologies for Internet of Things and Precision Agriculture: A Review 物联网与精准农业无线通信技术综述

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609421

D. Singh, R. Sobti

引用次数: 3

A Comprehensive Review on Encryption based Open Source Cyber Security Tools 基于加密的开源网络安全工具综述

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609369

Ritika Sharma, Sarishma Dangi, P. Mishra

引用次数: 3