2019 9th International Conference on Advances in Computing and Communication (ICACC)最新文献_第2页

An Unbiased and Time Efficient Task Allocation for Crowdsourcing Systems 众包系统的无偏时间效率任务分配

2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986188

Nellissery Cheryl Anto Jaya, G. Sajeev

引用次数: 0

A Methodology for Spikes and Transients Detection and Removal in Power Signals Using Chebyshev Approximation 用切比雪夫近似检测和去除功率信号中尖峰和瞬态的方法

2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986152

K. Sreelakshmi, T. T. Sasidhar, N. Mohan, K. Soman

引用次数: 0

Harvestable Black Pepper Recognition Using Computer Vision 利用计算机视觉识别可收获黑胡椒

2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986220

Shelbi Joseph, N. F. Jane Rose, P. Akhil

{"title":"Harvestable Black Pepper Recognition Using Computer Vision","authors":"Shelbi Joseph, N. F. Jane Rose, P. Akhil","doi":"10.1109/ICACC48162.2019.8986220","DOIUrl":"https://doi.org/10.1109/ICACC48162.2019.8986220","url":null,"abstract":"The objective of the research presented in this paper is to speed up recognition of harvestable black pepper using computer vision for automated black pepper harvesting. In this paper we introduce a novel dataset of black pepper images acquired using a digital camera. The proposed system is based on a combination of several image processing techniques and a deep learning model to achieve a system capable of recognizing and detecting harvestable black pepper from different elements of the scene, such as leaves, tree trunks branches and unripe pepper. The system is composed of a 3-stage image processing and a verification model in order to achieve 100% accuracy. This approach not only increase the accuracy but also reduce the processing time and computational resources required as the system moves from one stage to another only if a set of pre-defined conditions are met. After performing trial and error method on a number of different classifiers we decided to use ResNet-50, a CNN based classifier for the final validation of test results due to its immense speed and accuracy. The experimental results are showing promising 100% global accuracy with reasonable scan time which will enable real time application.","PeriodicalId":305754,"journal":{"name":"2019 9th International Conference on Advances in Computing and Communication (ICACC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131203854","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

ICACC 2019 Cover Page ICACC 2019封面

2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/icacc48162.2019.8986193

引用次数: 0

Plants Stress Response Detection by Selecting Minimal Bands of Hyperspectral Images 利用最小波段选择高光谱图像检测植物的胁迫响应

2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986161

M. Mondal, Manish Edida, Naman Sharma, Brejesh Lall, Dhandapani Raju

{"title":"Plants Stress Response Detection by Selecting Minimal Bands of Hyperspectral Images","authors":"M. Mondal, Manish Edida, Naman Sharma, Brejesh Lall, Dhandapani Raju","doi":"10.1109/ICACC48162.2019.8986161","DOIUrl":"https://doi.org/10.1109/ICACC48162.2019.8986161","url":null,"abstract":"It is an important task in the agricultural domain to determine the stress levels in plants. Drought conditions can have an adverse effect on crop yield. Hyperspectral Imaging (HSI) combined with classical Machine Learning algorithms are in current use to determine the stress levels. Every spectral band in an HSI does not contain useful information regarding the stress levels. For this reason, some vegetation indices are selected by agricultural researchers, based on reflectance ratios where a significant change in reflectance was observed because of stress. These indices do not always contain significant information because of changes in temperature, humidity or other atmospheric variations in different trials. There is no fixed set of vegetation indices which can be used to estimate stress levels accurately. In this paper, we demonstrated the working of Conditional Covariance Operator (CCM) which is used to select the most significant spectral bands from the collected Hyperspectral data itself. CCM is the most recent of the feature selection methods. This efficient feature selection method is used for the first time in this paper for plant stress analysis in rapid manner. It selects consistent discriminative spectral bands even when training examples per class are less than what other feature selection methods need. It can be seen that the Random Forest classifier model can classify the stress level into three categories (i) normal (ii) mild and (iii) severe stress with an accuracy of 99.7% when only 10 spectral bands are selected.","PeriodicalId":305754,"journal":{"name":"2019 9th International Conference on Advances in Computing and Communication (ICACC)","volume":"11 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123453992","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

Cost effective and reliable mobile solution for face recognition and authentication 具有成本效益和可靠的移动解决方案的人脸识别和身份验证

2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986206

N. Pradeesh, V. S. Sreejesh Kumar, Aswesh T. Anand, V. Geetha Lekshmy, Shivsubramani Krishnamoorthy, K. Bijlani

{"title":"Cost effective and reliable mobile solution for face recognition and authentication","authors":"N. Pradeesh, V. S. Sreejesh Kumar, Aswesh T. Anand, V. Geetha Lekshmy, Shivsubramani Krishnamoorthy, K. Bijlani","doi":"10.1109/ICACC48162.2019.8986206","DOIUrl":"https://doi.org/10.1109/ICACC48162.2019.8986206","url":null,"abstract":"Attendance marking is a critical and time-consuming process in schools and colleges. Manual attendance marking is time consuming, so as attendance recording using biometrics. Attendance marking using face recognition is time saving when compared to conventional methods. Most of the existing face recognition systems which uses static cameras are expensive and have portability issues too. To overcome this above mentioned time and portability constraints we propose an attendance marking system based on face recognition. The proposed system implemented as an android application takes input from the smart phone camera to mark the attendance. It uses Facenet Resnet V1 [10] convolutional neural network which was introduced by Google Inc, for face recognition. The attendance will be recorded in a learning management system(LMS) which serves as a back end application for the android application. After face recognition we are saving the attendance in our internal LMS system automatically. As per our analysis, we have noticed that the system works perfectly in a controlled scenario of 3-meter distance using a mobile camera device with a minimum face size of 108 × 108(Height × Width). In this controlled scenario our proposed methods achieves an accuracy over 90%.","PeriodicalId":305754,"journal":{"name":"2019 9th International Conference on Advances in Computing and Communication (ICACC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126062953","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

Quantitative Volume Measurement of Brain Tumor for Treatment and Planning 脑肿瘤定量体积测量在治疗和计划中的应用

2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986174

K. V. Ahammed Muneer, S. Pranav

{"title":"Quantitative Volume Measurement of Brain Tumor for Treatment and Planning","authors":"K. V. Ahammed Muneer, S. Pranav","doi":"10.1109/ICACC48162.2019.8986174","DOIUrl":"https://doi.org/10.1109/ICACC48162.2019.8986174","url":null,"abstract":"The disease progression of malignant tumors can be effectively indicated from their quantitative analysis. This article presents a faster and an accurate quantification of brain tumor volume from glioma MRI images. The tumor volume is a prime presaging factor for treatment of the disease and also to fix the treatment plans according to the severity of the disease. In our experimentation, we used T1-weighted glioma MRI images obtained from the hospital clinics. The first phase of the work comprising of the segmentation of tumor portion using semi-automatic methods like seeded region growing and morphological operations based algorithms. Secondly, the area of tumor portion of all tumor affected slices is calculated and this value is multiplied with the slice thickness to obtain the gross tumor volume. It should be noted that the slice thickness and pixel resolution depends on the MRI machine under test. The speed and accuracy for the volume measurement is analysed using the two mentioned segmentation algorithms. Results show that the morphological operations based method yields good segmented region compared to the region growing method. It is also observed that morphological operations based method is faster in segmenting the effective tumor region and hence to calculate the volume.","PeriodicalId":305754,"journal":{"name":"2019 9th International Conference on Advances in Computing and Communication (ICACC)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124422716","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

Accurate And Efficient Copy-Move Forgery Detection 准确和有效的复制-移动伪造检测

2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986157

Nidhi Anna Kurien, S. Danya, Diya Ninan, C. Heera Raju, Jisa David

{"title":"Accurate And Efficient Copy-Move Forgery Detection","authors":"Nidhi Anna Kurien, S. Danya, Diya Ninan, C. Heera Raju, Jisa David","doi":"10.1109/ICACC48162.2019.8986157","DOIUrl":"https://doi.org/10.1109/ICACC48162.2019.8986157","url":null,"abstract":"Today, due to the development of image processing applications like GIMP and Photoshop, forging of digital images with the absence of any trace is not at all difficult. Therefore crucial validation of content in a digital image is essential. Among the many prevailing forgery techniques, the copy-move forgery is recurrently occurring and it is easily performed. Detection of copy-move forgery is difficult as the forged region show similar properties to the source image. This paper analyzes the issue of copy-move forgeries and proposes an effective and reliable technique for its identification. Basically for the detection of copy-move forgery, two main approaches are applicable - block based and keypoint based techniques. Block-based technique employs division of image matrix into blocks that overlap and features are extracted. In keypoint based approach features of each keypoint is extracted for further matching. The aim is to implement two algorithms for detecting copy-move forgery - one using block based Discrete Cosine Transform algorithm and the other using the keypoint-based Scale Invariant Feature Transform. Efficiency of both algorithms are measured and their comparison is done using the GRIP and CoMoFoD databases. It was found that the Scale Invariant Feature Transform has more accuracy and precision compared to Discrete Cosine Transform method.","PeriodicalId":305754,"journal":{"name":"2019 9th International Conference on Advances in Computing and Communication (ICACC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131972908","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

Design and Implementation of Interleaver in GNU Radio for short block length Turbo codes GNU Radio中短块长度Turbo码交织器的设计与实现

2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986185

M. Sreedevi, B. Yamuna, P. Salija

引用次数: 2

Assessing Impact Of Explicit And Implicit Relationships On User’s Interests 评估显性和隐性关系对用户利益的影响

2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986153

Varnika Srivastava, V. Ladda, Vibush Shanmugam, Bhaskarjyoti Das

{"title":"Assessing Impact Of Explicit And Implicit Relationships On User’s Interests","authors":"Varnika Srivastava, V. Ladda, Vibush Shanmugam, Bhaskarjyoti Das","doi":"10.1109/ICACC48162.2019.8986153","DOIUrl":"https://doi.org/10.1109/ICACC48162.2019.8986153","url":null,"abstract":"A user’s interests are influenced by his relationships. A social network can be imagined to be made up of explicitly declared relationships as well as implicit relationships. Direct or explicit networks consist of explicitly declared friendship or follower relation. Hidden or implicit networks consist of similar users based on their similarity as decided by their footprints in the social network. In this work, the impact of user’s implicit network as compared to explicit network is investigated with respect to user’s behavior. Understanding this impact is of paramount significance for product driven websites such as Amazon, Yelp etc. These websites offer social networking features such as option to follow another user to enable product recommendation. In spite of such features, explicit networks on such websites deliver limited benefit for reasons such as very small fraction of users forming such explicit relationships and rapid staling of such explicit social links. Hence, these websites have to depend mostly on classical collaborative filtering techniques. In such scenario, an implicit network based on user activity footprints can be a viable alternative. In this work, an appropriate data set is chosen for this investigation based on the richness of the data set. The user’s interest is interpreted as the business that he frequents and the task of finding user’s interest is modelled as a link prediction problem between user and business. After detection of the networks, the network information (users’ relations) is captured using node embedding and then link prediction is performed. The baseline is provided by the explicit network. This investigation has looked at various combination of implicit and explicit networks to retain maximum information about users and their implicit/explicit relationships. It is observed that a certain combination that includes implicit network outperforms the baseline.","PeriodicalId":305754,"journal":{"name":"2019 9th International Conference on Advances in Computing and Communication (ICACC)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133091242","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