发布求助
文献互助 智能选刊 最新文献

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)最新文献

筛选
英文 中文
Human Pose Estimation in 3D using heatmaps 人体姿态估计在3D使用热图
2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760634
Sachin Parajuli, Manoj Kumar Guragai
{"title":"Human Pose Estimation in 3D using heatmaps","authors":"Sachin Parajuli, Manoj Kumar Guragai","doi":"10.1109/AISP53593.2022.9760634","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760634","url":null,"abstract":"3D human pose estimation involves estimating human joint locations in 3D directly from 2D camera images. The estimation model would have to estimate the depth information directly from the 2D images. We explore two methods in this paper both of which represent human pose as a heatmap. The first one follows (Newell et al. [6]) and (Martinez et al. [7]) where we predict 2D poses and then lift these 2D poses to 3D. The second approach is inspired by (Pavlakos et al. [8]) and involves learning 3D pose directly from the 2D images. We observe that while both these approaches work well, the mean of both their predictions gives us the best mean per-joint prediction error (MPJPE) score.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"36 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80920093","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
Simulation Analysis of Different TMDC Materials and their Performances 不同TMDC材料及其性能的仿真分析
2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760597
Vydha Pradeep Kumar, D. Panda
{"title":"Simulation Analysis of Different TMDC Materials and their Performances","authors":"Vydha Pradeep Kumar, D. Panda","doi":"10.1109/AISP53593.2022.9760597","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760597","url":null,"abstract":"The simulations and applications of nanostructured molybdenum disulfide particles and other complicated composite materials will be discussed in this paper. They have several appealing features that are related to the base element’s transfer characteristics, i.e. metal oxide semiconductor, and the strong chemical activity of Sulphur and oxygen family elements. The procedures followed in the creation then structuring of MoS2 nanoparticles and the mechanisms underpinning its biological characteristics and catalytic activity have made significant progress that helped us understand the properties of various materials. The most significant of this paper is that we will study the Simulation/Synthesis Analysis of Different TMDC Materials in different Model Design of FET Transistor and their applications. The benefits and prospects offered by MoS2 nanoparticles, nano-architectures, and other similar materials are discussed.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"5 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79450851","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
Forecasting Carbon Dioxide Levels Using Autoregressive Integrated Moving Average Model 利用自回归综合移动平均模型预测二氧化碳水平
2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760681
M. Ravi Kumar, S. Panda, Venkateswara Reddy Guruguluri, Namratha Potluri, Nagasree Kolli
{"title":"Forecasting Carbon Dioxide Levels Using Autoregressive Integrated Moving Average Model","authors":"M. Ravi Kumar, S. Panda, Venkateswara Reddy Guruguluri, Namratha Potluri, Nagasree Kolli","doi":"10.1109/AISP53593.2022.9760681","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760681","url":null,"abstract":"In the last few decades, the forecasting of lower atmospheric carbon dioxide (CO2) levels has been emphasized as an important topic among the atmospheric scientists and engineers for developing better predictive models in to predict the levels of CO2 keeping eye on the accelerated pollution. In the present work, we exploited the autoregressive integrated moving average (ARIMA) model capability for time-series prediction of CO2 level by considering the long-term recordings of air sample at Mauna Loa lab Observatory in Hawaii, USA, during the period from March 1958 to December 2001. The results reveal that forecasting of the parameter through ARIMA model has significantly improvements as compared to the existing techniques for such lower atmospheric parameters.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"28 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83093148","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
Honey Adulteration Detection using Hyperspectral Imaging and Machine Learning 利用高光谱成像和机器学习检测蜂蜜掺假
2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760585
Mokhtar A. Al-Awadhi, R. Deshmukh
{"title":"Honey Adulteration Detection using Hyperspectral Imaging and Machine Learning","authors":"Mokhtar A. Al-Awadhi, R. Deshmukh","doi":"10.1109/AISP53593.2022.9760585","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760585","url":null,"abstract":"This paper aims to develop a machine learning-based system for automatically detecting honey adulteration with sugar syrup, based on honey hyperspectral imaging data. First, the floral source of a honey sample is classified by a botanical origin identification subsystem. Then, the sugar syrup adulteration is identified, and its concentration is quantified by an adulteration detection subsystem. Both subsystems consist of two steps. The first step involves extracting relevant features from the honey sample using Linear Discriminant Analysis (LDA). In the second step, we utilize the K-Nearest Neighbors (KNN) model to classify the honey botanical origin in the first subsystem and identify the adulteration level in the second subsystem. We assess the proposed system performance on a public honey hyperspectral image dataset. The result indicates that the proposed system can detect adulteration in honey with an overall cross-validation accuracy of 96.39%, making it an appropriate alternative to the current chemical-based detection methods.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"60 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89878172","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
Real-Time Emotion Recognition from Facial Expressions using Artificial Intelligence 利用人工智能从面部表情中实时识别情绪
2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760654
Prashant Dhope, Mahesh B. Neelagar
{"title":"Real-Time Emotion Recognition from Facial Expressions using Artificial Intelligence","authors":"Prashant Dhope, Mahesh B. Neelagar","doi":"10.1109/AISP53593.2022.9760654","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760654","url":null,"abstract":"Emotion is the most important factor that distinguishes humans from robots. Machines are becoming more aware of human emotions as artificial intelligence advances. The objective of proposed method is to use artificial intelligence to build and construct a real-time facial emotion identification system. The proposed methodology has the capability of recognizing all the seven fundamental human face emotions. Those are angry, disgust, fear, happy, neutral, sad, and surprise. A self-prepared dataset is utilized to train the algorithm. The model is trained and facial expressions are recognized using a convolutional neural network. The real-time testing is accomplished using the Raspberry Pi 3B+ board and Pi-Camera. Using PyQt5, graphical user interface (GUI) is created for the system. The experimental result shows that, the proposed methodology has high recognition accuracy rate up to 99.88%.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"11 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88711422","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
A novel face recognition technique using Convolutional Neural Network, HOG, and histogram of LBP features 一种利用卷积神经网络、HOG和LBP特征直方图的人脸识别新技术
2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760679
S. Yallamandaiah, N. Purnachand
{"title":"A novel face recognition technique using Convolutional Neural Network, HOG, and histogram of LBP features","authors":"S. Yallamandaiah, N. Purnachand","doi":"10.1109/AISP53593.2022.9760679","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760679","url":null,"abstract":"Face recognition is a process of verifying an individual using facial images and it is widely employed in identifying people on social media platforms, validating identity at ATMs, finding missing persons, controlling access to sensitive areas, finding lost pets, etc. Face recognition is still a trending research area because of various challenges like illumination variations, different poses, and expressions of the person. Here, a novel methodology is introduced for face recognition using Histogram of Oriented Gradients (HOG), histogram of Local Binary Patterns (LBP), and Convolutional Neural Network (CNN). The features from HOG, histogram of LBP, and deep features from the proposed CNN are linearly concatenated to produce the feature space and then classified by Support Vector Machine. The face databases ORL, Extended Yale B, and CMUPIE are used for experimental work and attained a recognition rate of 98.48%, 97.33%, and 97.28% respectively.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"19 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87033450","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
Order Reduction of Continuous Interval Zeta Converter Model using Direct Truncation Method 用直接截断法降阶连续区间Zeta转换器模型
2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760520
V. Meena, Rishika Agrawal, Rajat Gumber, Anuja R. Tipare, Vinay Singh
{"title":"Order Reduction of Continuous Interval Zeta Converter Model using Direct Truncation Method","authors":"V. Meena, Rishika Agrawal, Rajat Gumber, Anuja R. Tipare, Vinay Singh","doi":"10.1109/AISP53593.2022.9760520","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760520","url":null,"abstract":"Zeta Converter consists of two inductors and two capacitors, hence it is a fourth order system. Output voltage of a zeta converter can be lower or higher as compared to the input voltage. In this paper, small signal dynamic model is obtained using steady state averaging technique and further direct truncation method is used to reduce the order of the given fourth order test case to first, second and third order systems respectively. Impulse response and step response are plotted as well as integral square error is calculated for lower and upper limit of reduced order transfer functions. The results presented prove the applicability and effectiveness of the proposed method.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"29 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82509459","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
Light Weight Encoder-Decoder for Underwater Images in Internet of Underwater Things (IoUT) 基于水下物联网(IoUT)的轻型水下图像编解码器
2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760532
Rashmi S. Nair, Rohit Agrawal, S. Domnic
{"title":"Light Weight Encoder-Decoder for Underwater Images in Internet of Underwater Things (IoUT)","authors":"Rashmi S. Nair, Rohit Agrawal, S. Domnic","doi":"10.1109/AISP53593.2022.9760532","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760532","url":null,"abstract":"Internet of Underwater Things (IoUT) explores the applications of Internet of Things (IoT) to monitor the sea animal habitat, observe atmosphere, and predict defense and predict defense and disaster. Raw underwater images are affected by absorption and dispersal of light due to underwater environment. Low power computational devices are preferred to cut down the cost of IoUT devices. Because of underwater environment nature, transmission of underwater images captured by underwater devices is considered as a big challenge. There is a need to provide solutions to amplify color, contrast and brightness aspects of captured underwater images to provide good visual understanding. Conventional compression techniques used for terrestrial environment, causes ringing artefacts due to the variable characteristics of underwater images. Deep image compression techniques consume more computational power and time, making them least efficient for low power computational devices. In this study, a low computational power and less time-consuming image compression technique is proposed to achieve high encoding efficiency and good reconstruction quality of underwater images. The proposed technique suggests using Convolutional Neural Network (CNN) at encoder side, which compresses and retains the structural data of the underwater image. And relative global histogram stretching based technique has been used at the decoder side to enhance the reconstructed underwater image. The proposed methodology is compared with conventional methods like Joint Pictures Experts Group (JPEG), Better Portable Graphics (BPG), Contrast Limited Adaptive Histogram Equalization (CLAHE) and deep learning techniques like Super Resolution Convolutional Neural Network (SRCNN) and Residual encoder-decoder methods to evaluate the reconstructed image quality. The presented work provides high quality image in comparison with both conventional and SRCNN method.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"53 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82646797","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
Design of a Wideband Periodic Cylindrical Conformal Fork shaped Antenna for WiMAX Application 用于WiMAX的宽带周期圆柱共形叉形天线设计
2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760528
Ratikanta Sahoo
{"title":"Design of a Wideband Periodic Cylindrical Conformal Fork shaped Antenna for WiMAX Application","authors":"Ratikanta Sahoo","doi":"10.1109/AISP53593.2022.9760528","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760528","url":null,"abstract":"A novel shape of wideband conformal antenna is presented in this article. The antenna is a wideband directional conformal fork shaped antenna. A combination of the concept of tapered slot antenna and dipole arrays are used to obtain directional radiation pattern. The dipole element is formed like a fork and has a semi-annular ring structure. As a result, instead of using a wire dipole, the concept of a log periodic antenna, uses three fork-shaped dipole elements in the proposed antenna. The proposed radial cylindrical conformal antenna is operating from 3.5 to 4.1 GHz achieves an impedance bandwidth of 600 MHz. The gain of the proposed radial cylindrical conformal antenna is around 4.7 to 5.6 dBi within the operating frequency.The halfpower beamwidth HPBW at 3.3 and 3.5 GHz are 122° and 116° in the H-plane and at E-plane are 56° and 57° respectively. The proposed cylindrical antenna is a reasonable antenna for WiMAX applications.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"36 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85044492","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 Evaluation of Speech Radio band Extension Technique using Simulink 基于Simulink的语音无线电频带扩展技术性能评价
2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760573
R. Emani, P. Telagathoti, N. Prasad
{"title":"Performance Evaluation of Speech Radio band Extension Technique using Simulink","authors":"R. Emani, P. Telagathoti, N. Prasad","doi":"10.1109/AISP53593.2022.9760573","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760573","url":null,"abstract":"The prime restriction characteristic of most communication systems is Bandwidth. In telephone networks, the functional voice frequency spreads in the interval 300 to 3400 Hz and is often referred to as In-Band (IB). The performance and perception of speech are extensively influenced by the IB. The Speech Radio Band Extension (SRBE) technique enforced alongside the IB speech signal aids in boosting the performance and perception of IB speech signals by sending strayed speech frequency components as extra data. At the receiver, an enhanced Wide Band (WB) signal is generated from the missing speech frequency components that are transmitted as additional information. Here both transmitter and receiver are implemented in the Simulink model. The competence of the SRBE technique is investigated in this research by comparing it with a Traditional Telephony Speech Enhancement Technique (TTSET). Subjective listening and objective testing assessments authenticate the improvement of the performance and perception of IB speech.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"56 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74455610","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
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信