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International Journal of Image, Graphics and Signal Processing最新文献

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Methodology for Translation of Video Content Activates into Text Description: Three Object Activities Action 视频内容活动转化为文本的方法描述:三个对象活动行动
International Journal of Image, Graphics and Signal Processing Pub Date : 2022-08-08 DOI: 10.5815/ijigsp.2022.04.05
Ramesh M. Kagalkar
{"title":"Methodology for Translation of Video Content Activates into Text Description: Three Object Activities Action","authors":"Ramesh M. Kagalkar","doi":"10.5815/ijigsp.2022.04.05","DOIUrl":"https://doi.org/10.5815/ijigsp.2022.04.05","url":null,"abstract":": This paper presents a natural language text description from video content activities. Here it analyzes the content of any video to identify the number of objects in that video content, what actions and activities are going on has to track and match the action model then based on that generate the grammatical correct text description in English is discussed. It uses two approaches, training, and testing. In the training, we need to maintain a database i.e. subject-verb and object are assigned to extract features of images, and the second approach called testing will automatically generate text descriptions from video content. The implemented system will translate complex video contents into text descriptions and by the duration of a one-minute video with three different object considerations. For this evaluation, a standard DB of YouTube is considered where 250 samples from 50 different domains. The overall system gives an accuracy of 93%.","PeriodicalId":378340,"journal":{"name":"International Journal of Image, Graphics and Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130522062","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
Optimal Call Failure Rates Modelling with Joint Support Vector Machine and Discrete Wavelet Transform 基于联合支持向量机和离散小波变换的最优呼叫失效率建模
International Journal of Image, Graphics and Signal Processing Pub Date : 2022-08-08 DOI: 10.5815/ijigsp.2022.04.04
Isabona Joseph, Agbotiname Lucky Imoize, Stephen Ojo, Ikechi Risi
{"title":"Optimal Call Failure Rates Modelling with Joint Support Vector Machine and Discrete Wavelet Transform","authors":"Isabona Joseph, Agbotiname Lucky Imoize, Stephen Ojo, Ikechi Risi","doi":"10.5815/ijigsp.2022.04.04","DOIUrl":"https://doi.org/10.5815/ijigsp.2022.04.04","url":null,"abstract":": Failure modeling is an essential component of reliability engineering. Enhanced failure rate modeling techniques are vital to the effective development of predictive and analytical methodologies, demonstration of the engineering procedure, allocation of procedures, design, and control of procedures. However, failure rate modeling has not been given adequate treatment in the literature. The need to investigate failure rate modeling leveraging cutting-edge techniques cannot be overemphasized. This paper proposed and applied a joint support vector regression (SVR) and wavelet transform (WT) approach termed (WT-SVR) to training and learning the call failures rate in wireless system networks. The wavelet transform has been accomplished using the wavelet compression sensing technique. In this technique, the standardized call failure rate data first go through a wavelet filtering transformation matrix. This is followed by separating and outputting the transformed filtered components in the compression phase. Finally, the transformed filtered output components were trained and evaluated using the SVR based on statistical learning theory. The resultant outcome revealed that the proposed WT-SVR learning method is by far better than using only the SVR method for call rate prognostic analysis. As a case in point, the WT-SVR attained STD values of 0.12, 0.21, 2.32, 0.22, 0.90, 0.81 and 0.34 on call failure data estimation compared to the basic SVR that attained higher STD values of 0.45, 0.98, 0.99, 0.46, 1.44, 2.32 and 3.22, respectively.","PeriodicalId":378340,"journal":{"name":"International Journal of Image, Graphics and Signal Processing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121490521","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
White Colour Hues in Displays and Lighting Systems Based on RGB and RGBW LEDs 基于RGB和RGBW led的显示和照明系统中的白色色调
International Journal of Image, Graphics and Signal Processing Pub Date : 2022-06-08 DOI: 10.5815/ijigsp.2022.03.01
A. Rybalochka, V. Kornaga, D. Kalustova, V. Mukhin, Y. Kornaga, V. Zavgorodnii, S. Valyukh
{"title":"White Colour Hues in Displays and Lighting Systems Based on RGB and RGBW LEDs","authors":"A. Rybalochka, V. Kornaga, D. Kalustova, V. Mukhin, Y. Kornaga, V. Zavgorodnii, S. Valyukh","doi":"10.5815/ijigsp.2022.03.01","DOIUrl":"https://doi.org/10.5815/ijigsp.2022.03.01","url":null,"abstract":"","PeriodicalId":378340,"journal":{"name":"International Journal of Image, Graphics and Signal Processing","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130562872","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
Mobile-Based Skin Disease Diagnosis System Using Convolutional Neural Networks (CNN) 基于手机的卷积神经网络皮肤病诊断系统(CNN)
International Journal of Image, Graphics and Signal Processing Pub Date : 2022-06-08 DOI: 10.5815/ijigsp.2022.03.05
Mwp Maduranga, D. Nandasena
{"title":"Mobile-Based Skin Disease Diagnosis System Using Convolutional Neural Networks (CNN)","authors":"Mwp Maduranga, D. Nandasena","doi":"10.5815/ijigsp.2022.03.05","DOIUrl":"https://doi.org/10.5815/ijigsp.2022.03.05","url":null,"abstract":". Skin cancer is a serious hazard to everyone throughout the world. However, it is difficult to make an accurate skin cancer diagnosis. Deep learning algorithms have recently excelled in several different tasks. They've also been used for skin disease diagnosis jobs mainly. With around 85% accuracy, the suggested technique outperforms existing methods on the HAM10000 dataset. Its resilience in detecting the impacted region considerably faster with nearly 2x fewer computations than the standard MobileNet model results in low computing efforts. A mobile application, on the other hand, is built for quick and accurate action. By looking at an image of the afflicted area at the beginning of a skin illness, it assists patients and dermatologists in determining the kind of disease present. According to these findings, the suggested approach can assist general practitioners in quickly and accurately diagnosing skin diseases, therefore avoiding future complications and mortality.","PeriodicalId":378340,"journal":{"name":"International Journal of Image, Graphics and Signal Processing","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124104687","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: 8
Comparison of Circular and Linear Orthogonal Polarization Bases in Electromagnetic Field Parameters Measurement 圆形和线性正交极化基在电磁场参数测量中的比较
International Journal of Image, Graphics and Signal Processing Pub Date : 2022-06-08 DOI: 10.5815/ijigsp.2022.03.06
L. Ilnitsky, O. Shcherbyna, F. Yanovsky, M. Zaliskyi, Oleksii Holubnychyi, O. Ivanets
{"title":"Comparison of Circular and Linear Orthogonal Polarization Bases in Electromagnetic Field Parameters Measurement","authors":"L. Ilnitsky, O. Shcherbyna, F. Yanovsky, M. Zaliskyi, Oleksii Holubnychyi, O. Ivanets","doi":"10.5815/ijigsp.2022.03.06","DOIUrl":"https://doi.org/10.5815/ijigsp.2022.03.06","url":null,"abstract":"","PeriodicalId":378340,"journal":{"name":"International Journal of Image, Graphics and Signal Processing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128959133","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
Multi-Module Convolutional Neural Network Based Optimal Face Recognition with Minibatch Optimization 基于多模块卷积神经网络的小批量优化人脸识别
International Journal of Image, Graphics and Signal Processing Pub Date : 2022-06-08 DOI: 10.5815/ijigsp.2022.03.04
Deepa Indrawal, Archana Sharma
{"title":"Multi-Module Convolutional Neural Network Based Optimal Face Recognition with Minibatch Optimization","authors":"Deepa Indrawal, Archana Sharma","doi":"10.5815/ijigsp.2022.03.04","DOIUrl":"https://doi.org/10.5815/ijigsp.2022.03.04","url":null,"abstract":"","PeriodicalId":378340,"journal":{"name":"International Journal of Image, Graphics and Signal Processing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115974948","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: 4
Speech Enhancement through Implementation of Adaptive Noise Canceller Using FHEDS Adaptive Algorithm 利用FHEDS自适应算法实现自适应降噪的语音增强
International Journal of Image, Graphics and Signal Processing Pub Date : 2022-06-08 DOI: 10.5815/ijigsp.2022.03.02
C. Umasankar, M. S. Sai ram
{"title":"Speech Enhancement through Implementation of Adaptive Noise Canceller Using FHEDS Adaptive Algorithm","authors":"C. Umasankar, M. S. Sai ram","doi":"10.5815/ijigsp.2022.03.02","DOIUrl":"https://doi.org/10.5815/ijigsp.2022.03.02","url":null,"abstract":": Speech analysis is the modelling and estimating of the different speech characteristics that would provide the importance on each set of criteria established on the real time applications. One such analytic section in enhancement process on speeches would improve the need of speech enhancement. This paper compares the performance analysis of our proposed Fast Hybrid Euclidean Direction Search (FHEDS) algorithm with other adaptive algorithms such as NHP and FEDS algorithm. These algorithms have been tested for their adaptive noise cancellation of speech signal corrupted by different noises such as Babble, Factory, Destroy Engine, Car, Fire Engine and Train Noises. Ensuring the design criteria with current design limits of the database and its analysis have been encapsulated with each phase of design with Noise model, improving the better performance aspects. The relative factors for comparisons have been tabulated with each set of the noise and clear speech data with proposed filter operation. The proposed model effectively reduces the noise for achieving better speech enhancement. The proposed model achieves high Signal-to-Noise Ratio (SNR) when compared to traditional models.","PeriodicalId":378340,"journal":{"name":"International Journal of Image, Graphics and Signal Processing","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115568987","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
Channel Estimation of massive MIMO Using Code Shift Keying Pilot Symbols (CSK-PS) 基于码移键控导频符号(CSK-PS)的大规模MIMO信道估计
International Journal of Image, Graphics and Signal Processing Pub Date : 2022-06-08 DOI: 10.5815/ijigsp.2022.03.03
Jagadeesh Chandra Prasad Matta, S. P
{"title":"Channel Estimation of massive MIMO Using Code Shift Keying Pilot Symbols (CSK-PS)","authors":"Jagadeesh Chandra Prasad Matta, S. P","doi":"10.5815/ijigsp.2022.03.03","DOIUrl":"https://doi.org/10.5815/ijigsp.2022.03.03","url":null,"abstract":": The increasing demand for bandwidth by mobile users in wireless communication becomes a challenging issue to the research community. Several theories and models have been proposed to mitigate this issue. The most effective and commonly used approach to resolve the demand shortage of bandwidth is the massive Multi-Input and Multi-Output (MIMO) approach in which the number of transmitting and receiving antennas is placed at the base station (BS) to fulfill the issue of bandwidth. However, this technique suffers from various issues in estimating the channel due to interference, beamforming, and pilot contamination. In this paper, a novel channel estimation technique is being proposed using Code Shifting Keying symbols as pilot signals (CSK-PS) to minimize the pilot contamination. These signals are used as reference signals and the received signal is detected. The presented approach reduces the interference (pilot contamination) and improves the channel estimation in massive MIMO networks by using the modified expected propagation estimation method (MEPE). The presented approach is validated using mat-lab.","PeriodicalId":378340,"journal":{"name":"International Journal of Image, Graphics and Signal Processing","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115252663","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
Recent Object Detection Techniques: A Survey 最新目标检测技术综述
International Journal of Image, Graphics and Signal Processing Pub Date : 2022-04-08 DOI: 10.5815/ijigsp.2022.02.05
Diwakar, Anshu Gupta
{"title":"Recent Object Detection Techniques: A Survey","authors":"Diwakar, Anshu Gupta","doi":"10.5815/ijigsp.2022.02.05","DOIUrl":"https://doi.org/10.5815/ijigsp.2022.02.05","url":null,"abstract":"","PeriodicalId":378340,"journal":{"name":"International Journal of Image, Graphics and Signal Processing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121035303","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
Towards Query Efficient and Derivative Free Black Box Adversarial Machine Learning Attack 基于查询高效和无导数的黑盒对抗机器学习攻击
International Journal of Image, Graphics and Signal Processing Pub Date : 2022-04-08 DOI: 10.5815/ijigsp.2022.02.02
Amir F. Mukeri, Dwarkoba P. Gaikwad
{"title":"Towards Query Efficient and Derivative Free Black Box Adversarial Machine Learning Attack","authors":"Amir F. Mukeri, Dwarkoba P. Gaikwad","doi":"10.5815/ijigsp.2022.02.02","DOIUrl":"https://doi.org/10.5815/ijigsp.2022.02.02","url":null,"abstract":"","PeriodicalId":378340,"journal":{"name":"International Journal of Image, Graphics and Signal Processing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114193460","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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