Volume-7 , Issue-4 , Apr - 2019 Go Back

Nowadays a lot of organizations are in a constant lookout to simplify their hiring process so that they can scout the best talent in a minimum time frame. The proposed system tries to simplify the manual work by automating the entire hiring process. The system helps to clean, parse and classify the large amount of resumes, that the hiring managers’ receive on a daily basis, using SVM (support vector machine algorithm in python).The system would cover some repetitive manual procedures like the aptitude test using JavaScript and the audio HR interview using natural language processing and sentiment analysis. This would ensure that the HR managers would not have to ask the same questions repeatedly thus preventing them from losing good candidates due to lack of interest towards the end of the interview. The system also provides detailed analysis in the form of a bar graph which gives a score count of the analysed tone parameters on the basis of the audio interview provided by the candidate.

Natural Language Processing, Support Vector Machine, Tone Analysis, Resume, Classification, Sentiment Analysis.

[1] Prarthita Das and Amala Deshpande,” Automated Filtering of Relevant Resumes” International Journal of Computer Applications Volume 154 – No.6, November 2016
[2] Sunil Kumar Kopparapu, “Automatic Extraction of Usable Information from Unstructured Resumes to Aid Search”, published in IEEE 2010.
[3] Mayuri Verma “Cluster based Ranking Index for Enhancing Recruitment Process using Text Mining and Machine Learning” International Journal of Computer Applications (0975 – 8887) Volume 157 – No 9, January 2017
[4] Apoorv Agarwal, Boyi Xie Ilia Vovsha, Owen Rambow Rebecca Passonneau, “Sentiment Analysis of Twitter Data” IEEE ICASSP journal
[5] Lakshmish Kaushik, Abhijeet Sangwan, John H. L. Hansen,” SENTIMENT EXTRACTION FROM NATURAL AUDIO STREAMS ”, CP-ICASSP13
[6] Mishne and Glance, “Predicting movie sales fromblogger sentiment," in AAAI 2006 Spring Symposiumon Computational Approaches to Analyzing Weblogs, 2006.
[7] Online paper reviews using sentiment analysis, (IJACSA) International Journal of Advanced Computer Science and Applications,Vol. 6, No. 9
[8] White paper-pymetrics: Using Neuroscience and Data Science
to Revolutionize talent Management.

[9] Ketan Sarvakar and Urvashi K Kuchara,” Sentiment Analysis of movie reviews: A new feature-based sentiment classification” International Journal of Scientific Research in Computer Sciences and Engineering Vol.6, Issue.3, pp. 8-12 , June (2018).

[10] Amit Palve, Rohini D.Sonawane ,Amol D. Potgantwar,” Sentiment Analysis of Twitter Streaming Data for Recommendation using Apache Spark” International Journal of Scientific Research in Network Security and Communication Volume-5, Issue-3, June 2017.

Siddhi Khanvilkar, Suparna Shetty, Disha Solanki, Sarika Davare , "Smart Recruitment System," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.823-828, 2019.

A popular technology called Wi-Fi is nothing but the information carrier between transmitter and receiver. Through this paper, we show that Wi-Fi can also extend our senses, enabling us to see moving objects through walls and behind closed doors. So can we use Wi-Fi signals to identify people in a closed room with their relative location? Yes, we can achieve the identification of objects in closed rooms through a technology called Wi-Vi. One can also identify simple gestures and combine a sequence of gestures behind the wall to communicate messages. This introduces two main innovations. Initially, it uses MIMO interference nulling to eliminate the static object reflections and target the focus on moving objects. Next, it shows how one can track a human by treating the motion of a human body as an antenna array and tracking the resulting RF beam. It helps in various applications which are given in the papers that helps the human to save life in critical conditions.

MIMO

[1] Sudarshan Adeppa, “Detection of Objects across the Walls with Wi-Fi Technology”, International Journal on Emerging Technologies, 2015.
[2] K. Chetty, G. Smith, and K. Woodbridge, “Through-the-wall sensing of personnel using passive bistatic Wi-Fi-radar at standoff distances,” IEEE Trans. Geoscience and Remote Sensing, 2012.
[3] Adib, Fadel, and Dina Katabi, “See through Walls with Wi-Fi,” Proceedings of the ACM SIGCOMM Conference, 2013.
[4] S. Ram and H. Ling, “through-wall tracking of human movers using join doppler and array processing,” IEEE Geoscience and Remote Sensing Letters, 2008
[5] G. Char vat, L. Keppel, E. Rothwell C. Coleman, and E. Mohole. An ultra-wideband (UWB) switched-antenna-array radar imaging system in IEEE ARRAY, 2010
[6] M Murugan, Mr. G Sathish “See-through wall using Wi-Vi” International Journal of Scientific & Engineering Research Volume 9, Issue 4, April-2018
[7] Manupalli Uma Maheshwar Rao, Bala Brahmeswara kadaru” A study on future scope of Wi-Vi technology” International Research Journal of Engineering and Technology (IRJET), 2017
[8] Arpitha Shankar S I “MIMO Cognitive Radio with Low-Cost Reception Using Beam Forming and Antenna Sub Array Formation” International Journal of Computer Sciences and Engineering (IJCSE), 2016

Vidyasagar S D, Seema, "A Study on Applications of Wi-Vi Technology," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.829-834, 2019.

One of the most popular renewable energy is solar energy due to its large availability. Major benefit of PV system for adopting solar energy is due to less maintenance cost, no moving parts and small limitations for installation. However, photovoltaic system has poor conversion efficiency as output performance of PV system is dependent on solar irradiation and temperature which are not consider as constant input source to system. The main objective is to extract maximum power from PV system Various techniques are to be used as mechanically as well as electrically to extract maximum power. Conventional Perturb and Observation (P&O), incremental conductance, adaptive Perturb and Observation, fuzzy logic based algorithm has implemented for extraction of maximum power. Boost converter is used for power interface as well as to step up the output voltage. Fuzzy logic based algorithms finds successful role to track maximum power even in rapidly changing climatic conditions. The proposed model has been implemented in MATLAB/Simulink and validated with experimental data of commercial PV panels.

PV(photovoltaic) module, Mathematical Modeling, Maximum power extraction, Perturb & Observation, Incremental conductance, Adaptive Perturb and Observation, Fuzzy logic algorithm, Simulation.

[1] Trishan Esram, Patrick L. Chapman, “Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques”, IEEE Transaction on Energy conversion, 22(2), 439–449, 2007.
[2] Marcelo Gradella Villalva, Jonas Rafael Gazoli, Ernesto Ruppert Filho, “Comprehensive Approach to Modeling and Simulation of Photovoltaic Arrays”, IEEE Transaction On Power Electronics, 24(5), 1198–1208, MAY 2009.
[3] N. Pandiarajan, Ranganath Muthu, “Mathematical Modeling of Photovoltaic Module with Simulink”, 1st International conference on Electrical Energy Systems, March 2011.
[4] Javier Cubas, Santiago Pindado,Carlos de Manuel, “Explicit Expressions for Solar Panel Equivalent Circuit Parameters Based on Analytical Formulation and the Lambert W-Function”, 1st International e-Conference on Energies, 2014.
[5] Jaw-Kuen Shiau, Yu-Chen Wei and Bo-Chih Chen, “A Study on the Fuzzy-Logic-Based Solar Power MPPT Algorithms Using Different Fuzzy Input Variables”, April 2015.
[6] Md Tofae l Ahmed, Teresa Gonçalves, Mouhaydine Tlemcani, “Single Diode Model Parameters Analysis of Photovoltaic Cell”, IEEE 5th International Conference on Renewable Energy Research and Applications , Nov2016.
[7] H.A.Mohamed, H.A.Khattab, A.Mobarka, G.A.Morsy, “Design, Control and Performance Analysis of DC-DC Boost Converter for Stand-Alone PV System”, Eighteenth International Middle East Power Systems Conference (MEPCON), Dec 2016.
[8] Pooja Sahu, Deepak Verma, Dr.S Nema, “Physical Design and Modelling of Boost Converter for Maximum Power Point Tracking in Solar PV systems”, International Conference on Electrical Power and Energy Systems (ICEPES), Dec 2016.
[9] S Narendiran, Sarat Kumar Sahoo, Raja das, Ashwin Kumar Sahoo, “Fuzzy Logic Controller based Maximum Power Point Tracking for PV systems”,3rd International Conference on Electrical Energy Systems(ICEES)-2016.
[10] Maria C. Argyrou, Paul Christodoulides, Soteris A. Kalogirou, “Modeling of a photovoltaic system with different MPPT techniques using MATLAB/Simulink”, IEEE International Energy Conference(ENERGYCON), June 2018.

Dhruv M. Dhivar, M.B. Jhala, M. K. Kathiria, "Maximum Power Extraction from PV System Using Fuzzy Logic," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.835-840, 2019.

Player Selection is one of the most important tasks for any sport. The success or failure of any team lies in the skills and abilities of the players that comprise the team. The performance of the players depends on various factors and characteristics of a player. The team management select required players for each match from a squad of 7-20 players. Depending on different sports they analyze different characteristics and the statistics of the players to select the best players for each match who can shine on international stage. The process of player selection and team formation in multilayer sports is a complex multi-criteria problem where the ultimate success is determined by how the collection of individual players forms an effective team. The proposed system is formulated that takes into account various available performance data of players gives an optimize and balance team without any human interference which is limited to entering performance data. This system proposes Machine learning technology by implementing Support Vector Machine(SVM) algorithm for efficient player selection. Our system thus can effectively take into account all factors involved and give the optimal team, without human interference.

Machine Learning, SVM (SUPPORT VECTOR MACHINE), Player Selection.

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[4]http://aya.technion.ac.il/karniel/CMCC/SVM-tutorial.pdf
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Farhana Siddiqui, Hasan Phudinawala, Chetan Davale , Soham Pawar, "Innovative Idea for Playerelection using Support Vector Machine(Svm)," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.841-843, 2019.

Breast cancer is one of the leading diseases among the worldwide disease; the breast cancer is occur will both gender but it is very rare for man. The breast cancer is an unwanted tissue is growth on the breast. The survival rate has increased above 500,000 around the world. When detected early, the five-year continued existence rate for breast cancer exceeds 80% of cases. Early analysis of breast cancer is serious for the continued existence of the patient. It is formed the multiple cells which may it occur on benign and malignant. The malignant is a cluster of cells and it is irregular shape. The benign tumor is oval shaped and smooth surface. In our approach, the medical microwave imaging technique is an innovative technology for detecting cancer it is avoiding for the patient uncomfortable feelings and screening is very easy. It is analysis the tissue by using the radio-frequencies and differentiates either benign or malignant. The deep learning is an important role for bio-medical images, classification and gains the human approaches. The grey level co-occurrence matrix is a feature extraction to reduce the noise detection and apply the grey color for differentiate the cancerous tissue and non-cancerous tissue . The back propagation algorithm is trained the network randomly and minimized the error rate. For each classifier, the presentation factor such as sensitivity, specificity and accuracy are computed. It is observed that the proposed scheme with classifier outperforms specificity to classify microwave images as normal or abnormal.

breast cancer, medical microwave images, grey level co-occurrence matrix(GLCM), Back propagation.

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K. Anastraj, T. Chakravarthy, "Analysis the Breast Cancer using Back Propagation with Deep Neural Network," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.844-847, 2019.

Growth in the cloud computing evidenced in the recent past has accentuated the need for higher levels of security for obvious reasons. Various algorithms and techniques have been developed by the researchers to provide the security at multiple ends in multiple locations of the cloud data. The researchers have attempted to provide the security using various methodologies developed over time. However, there are frequent breaches of security in the recent times observed globally. Though the use of finger reference key in the security of data over the cryptography algorithm has enhanced the level of security, yet there are still loopholes in the framework providing opportunity for hackers for unauthorized access. In this paper, we propose a methodology to enhance the security by introducing the random security codes on the existing security framework. We establish that this procedure is more robust as compared to only using the finger reference key suggested by previous researchers and analysts.

Cloud Computing, Random Security Code, Data Hiding

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[2] Siddharth V., “Seven Cyber security trends that India will witness in 2019”, PWC Report, 2018.
[3] Mudasir Ahmed Muttoo, Pooja Ahlawat, ” A Secure Information Hiding Approach in Cloud Using LSB”, International Journal of Science and Research, Vol. 4, Issue.,7, pp.1171-1776,2013.
[4] Nazir Mohsin, “Cloud Computing: Overview & Current Research Challenges “,IOSR Journal of Computer Engineering, Vol. 8, Issue.,1, pp. 14-22,2012.
[5] Ashik Mohamed M., Sankara Nayanan A., Nithyananda Kumari, ”Typical Security Measures Of Cloud Computing”,International Journal of Computer Trends and Technology, Vol. 5, No.,6, pp.299-304, 2013.
[6] Geeta C. M., RaghavendraS, RajkumarBuyya, Venugopal K R, S SIyengar, L M Patnaik,“Data Auditing and Security in Cloud Computing: Issues, Challenges and Future Directions”, International Journal of Computer, Vol. 28, No.,1,pp.8-57, 2018.
[7] Kiran, Sandeep Sharma, “A Comparative Review Of Various Approaches To Ensure Data Security In Cloud Computing “, International Journal of Engineering Research and General Science, Vol.5, Issue.,2, pp.124-130, 2017.
[8] Ayman Ibaida, Ibrahim Khalil, ”Wavelet-Based ECG Steganography for Protecting Patient Confidential Information in Point-of-Care Systems” , IEEE Transactions on Biomedical Engineering ,Vol. 60 , Issue., 12, pp.3322-3330, 2013.
[9] Ahmed Monjur, Mohammad Ashraf Hossain,“Cloud Computing and Security Issues in the Cloud” International Journal of Network Security & Its Applications, Vol.6, No., 1, pp.25-36,2014.
[10] Mudasir Ahmed Muttoo, Pooja Ahlawat,” A Secure Information Hiding Approach in Cloud Using LSB”, International Journal of Science and Research, Vol. 4, Issue.,7, pp.1171-1776,2013.
[11] C.-C. Chang, C.-C. Lin, C.-S. Tseng, W.-L. Tai, “Reversible hiding in DCT-based compressed images”, Information Sciences, Vol. 177, Issue., 13, pp. 2768–2786, 2007.
[12] Deepika,” Enhancement of Data Security for Cloud Environment Using Cryptography and Steganography Technique” International Journal of Innovative Research in Computer and Communication Engineering, Vol. 5, Issue.,1, pp.225-237, 2017.
[13] Hamlen, Murat Kantarcioglu, Latifur Khan, Bhavani Thuraisingham,” Security Issues for Cloud Computing”, International Journal of Information Security and Privacy, Vol. 4, Issue.,2, pp. 39-51, 2010.
[14] Wid A. Awadh, Ali S. Hashim,” Using Steganography for Secure Data Storage in Cloud Computing”, International Research Journal of Engineering and Technology, Vol. 4, Issue., 4, pp. 3668-3772, 2017.
[15] Lubacz Józef; Wojciech Mazurczyk ; Krzysztof Szczypiorski,” Principles and overview of network steganography”, INSPEC, Vol. 52 , Issue., 5 , pp. 225 – 229,2014.
[16] Athanasios Vasilakos, Muhammad Baqer Mollah, Md. Abul Kalam Azad, “Secure Data Sharing and Searching at the Edge of Cloud-Assisted Internet of Things”, IEEE Cloud Computing, Vol. 4, Issue.,1,pp. 34-43, 2017.
[17] Pankaj Arora, RubalChaudhry, Wadhawan Er. Satinder Pal Ahuja,” Cloud Computing Security Issues in Infrastructure as a Service”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol.2, Issue.,1, 2012.
[18] Ramalingam Sugumar, K. Arul Marie Joycee, “FEDSACE: A Framework for Enhanced user Data Security algorithms in Cloud Computing Environment”, International Journal on Future Revolution in Computer Science & Communication Engineering, Vol. 4, Issue., 3, pp. 49-52, 2018.
[19] Baowei Wang,Zhihua Xia ,Xinhui Wang and Xingming Sun, ”Steganalysis of least significant bit matching using multi order differences”, Wiley online liabrary,2013; https://doi.org/10.1002/sec.864.
[20] Mandy Douglas, Karen Bailey, Mark Leeney, Kevin Curran,” An overview of Steganography techniques applied to the protection of biometric data” July 2018, Volume 77, Issue 13, pp 17333–17373.
[21] Balaji. S, Mandy Sonio Newcastle,”SECURE DATA TRANSMISSION BY STEGANOGRAPHY USING PRIVATE KEY IN CLOUD” International Journal of Pure and Applied Mathematics,Vol. 119, No., 14, pp. 1653-1660, 2018.
[22] Nancy Garg, Kamalinder Kaur, ”Data Storage Security Using Steganography Techniques”, International Journal of Technical Research and Applications, Vol. 4, Issue.,6, pp. 93-98, 2016.
[23] A. Mahesh Babu, G.A. Ramachandra, M. Suresh Babu, “Implementation of Security in Cloud Systems Based using Encryption and Steganography”, International Journal of Electrical, Electronics and Computer Systems, Vol. 3, Issue., 11, 80-84, 2015.
[24] Shelly, Rajesh Kumar Bawa,” Secure Image Transmission for Cloud Storage System Using Hybrid Scheme”, International Journal of Engineering Research and Development, Vol. 11, Issue., 9, pp. 18-26, 2015.
[25] Gowthami Garikapati, Yakobu D, Gnaneswara Rao Nitta, Amudhavel J,” AN ANALYSIS OF CLOUD DATA SECURITY ISSUES AND MECHANISMS”, International Journal of Pure and Applied Mathematics, Vol. 116, No. 6, pp. 141-147,2017.
[26] Ayush Gupta, Arvind Kumar, “Information Security using the ensemble approach of Steganography and Cryptography”, in the proceedings of International Conference on Sustainable Computing in Science, Technology & Management, SUSCOM-2019, pp. 66-73, 2019, http://dx.doi.org/10.2139/ssrn.3350895.
[27] Pramod Ambadas Rao Pawar, Aparna G. Korde, “A Solution to Cloud Security: Image Steganography”, International Journal of Multidisciplinary Research, Vol. 2, Issue. ,2, pp.83-90, 2016.
[28] Mohammad Obaidur Rahman, Muhammad Kamal Hossen, Md. GolamMorsad, Animesh Chandra Roy, Md. Shahnur Azad Chowdhury, “An Approach for Enhancing Security of Cloud Data using Cryptography and Steganography with E-LSB Encoding Technique “, IJCSNS International Journal of Computer Science and Network Security, Vol. 18, No.9, pp.85-93, 2018.
[29] Adamu Ismail Abdulkarim, Boukari Souley, “An Enhanced Cloud Based Security System Using RSA as Digital Signature and Image Steganography”, International Journal of Scientific & Engineering Research, Vol. 8, Issue.,7, pp. 1512-1517, 2017.
[30] Anuradha Porwal, “Hybrid Protocol Employing Steganography &Cryptography for Cloud Storage Security”, International Journal of Advanced Research in Computer Science & Technology, Vol. 4, Issue.,2, pp. 208-209, 2016.
[31] Steffen Wendzel, Wojciech Mazurczyk, Luca Caviglione, Michael Meier, “Hidden and Uncontrolled – On the Emergence of Network Steganography Threats”, ISSE 2014 Securing Electronic Business Processes Conference Proceedings, pp. 123-133.
[32] Dhivyaprabha E. , R. Madhubala, M. Abarna, “Security Framework for Cloud Data Sharing”, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, Vol.3,Issue.3, pp. 665-671, 2018.
[33] Mishra Ajeet , Umesh Kumar Lilhore, Nitesh Gupta, “Review of Various Data Storage and Retrieval Method for Cloud Computing”, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, Vol.2,Issue.5, pp. 584-588, 2017.
[34] Varsha Yadav, Preeti Aggarwal,” Fingerprinting Based Recursive Information Hiding Strategy in Cloud Computing Environment”, International Journal of Computer Science and Mobile Computing, Vol. 3, Issue., 5, pp. 702 – 707, 2014.

Arvind Kumar, Ayush Gupta, "Extended Information Hiding Procedure in Cloud Computing Environment using Random Security Codes," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.848-853, 2019.

Behavioural biometrics takes the authentication one step further, requiring the user to not only have the right fingerprint to logon, but to prove that they are the same person whom they claim to be throughout the duration of the session. This takes into account the way in which a person interacts with a device, such as the force with which they hit a key, the angle they use to swipe a touch screen, or their typing speed. Tracking and analyzing these areas allows users to safely use the same password their behaviour for every login. We need to change the way we think about security across passwords, static and behavioural biometrics. Since virtually every authentication technique can be compromised, user should not rely solely on any single control for authorizing, but adopt a layered approach to security, combining the various available authentication technologies to improve both accuracy and user experience.

Android, Sensors, API, SQLite, Java

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Shikha Agarawal, Ashwin Gujarathi, Abhilash Dhumane, Pramil Bhosure, Mangesh Vinchankar, "Active Authentication on Mobile Device using Stylometry," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.854-858, 2019.

Assurance of blood classification is critical before managing a blood transfusion in a crisis circumstance. Right now, these tests are performed physically by specialists in the lab, when the test is taken care of with a substantial number of tests, it is dreary to do and it might prompt human mistakes. In this paper, the proposed thought is to supplant the manual work in clinical research centers for distinguishing the blood gathering. The proposed framework expects to build up an inserted framework which utilizes Image preparing calculation to perform blood tests dependent on ABO and Rh blood composing frameworks. The proposed framework intends to build up an implanted framework which utilizes Image handling calculation to perform blood tests dependent on ABO and Rh blood composing frameworks. In this paper different existing methods are reviewed and their performance are evaluated so that it can help the researchers in their work.

Antigen, Blood Samples, GPU, Histogram, LBP (nearby paired example), Nearest Neighbor Classifier, Image Processing, Pattern Matching.

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Ruchi Jogi, Avinash Dhole, "Blood Group Detection using Image Processing Techniques: A Review," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.859-863, 2019.

In Wireless Local Area Networks (WLANs), the clients can speak each other by using the Access Point [AP] easily. Since it uses wireless medium for words there are lots of security challenges exists. WLANs provide speed equal to wired LANs and allow wireless devices to be mobile. Even though it is very useful, there are lots of security attacks specially it is vulnerable to distributed Denial of Service (DDOS) attacks, this leads to unavailability of a service or resource by how of either crashes a service or by flooding the network with unwanted traffic to slowing down the delivery of service to the client. A distributed denial of service attack is the one in which the attacker attacks the victim by many sources. In this paper, we deployed WLANs in infrastructure mode as the extension of wired local area network. It was done in experimental approach to detect and prevent DDoS attack by using Intrusion Detection and Prevention System (IDPS) and Machine Authentication Code(MAC) with Service Set Identifier (SSID) was studied and simulated utilizing OPNET 17.5 simulator. The IDPS on the server distinguishes legitimate users from the illegal user by the registered MAC. If the client is illegal, then it withdraws the user from the connection. And the access point will not show SSID. The SSID should be hidden by the Admin and will be given to only the registered users with MAC Address. Our Proposed solution can enhance the security of DDoS and can secure the WLAN from the Attackers.

Distributed Denial of Service (DDOS), Intrusion Detection and Prevention System( IDPS), OPNET ,Service Set Identifier (SSID), Machine Authentication Code(MAC) and Wireless Local Area Networks (WLANs).

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Feven Teferi, J. Sebastian Nixon , "A Security Mechanism to Mitigate DDoS Attack on Wireless Local Area Network (WLAN) using MAC with SSID," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.864-869, 2019.

With the use of deep learning networks image processing tasks has improved due to the development of learning feature illustration from images. Generally, in the real world scenario, these images available to classify is prone to noise and other deformities. According to many types of research in the past, the deep neural networks (DNNs) are found effective for image classification problems, but they suffer from the same real-life problem of noise and other deformities in an image. Noise is common occurrences in real life situations and many studies have been carried out in the past few decades with the purpose to remove the effect of noise in the image data. In this paper, the aim was to examine the DNN-based improved noisy image classification model. We have used a hybrid of denoising autoencoder, convolutional denoising autoencoder then using a classifier which is a combination of two different architectures one is Convolutional Neural Network (CNN) and the other is extreme Gradient Boosting (XGBOOST). This technique gives progressively better outcome by incorporating CNN as a trainable element for feature extraction from the image in input and XGBoost used as an identifier at the last stage of the model for outcomes.

Blurry Images, Image Classification, Noisy Images, Supervised Classification, Unsupervised Classification, Image Denoising

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Mayur Thakur, Sofia K. Pillai , "A Hybrid System Using CNN and AE for Noisy Image Classification," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.870-875, 2019.