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Forgery detection in medical images using Complex Valued Neural Network (CVNN) by Olanrewaju, Rashidah Funke, Khalifa, Othman Omran, Hassan Abdalla Hashim, Aisha, Zeki, Akram M., Aburas, Abdurazzag Ali

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An ensemble feature selection method to detect web spam by Oskouei, Mahdieh Danandeh, Razavi, Seyed Naser

“…With regard to increasing available information in virtual space and the need of users to search, the role of search engines and used algorithms are important in terms of ranking. Web spam is an illegal method to increase mendacious rank of internet pages by deceiving the algorithms of search engines, so it is essential to use an efficient method. …”
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Human Spontaneous Emotion Detection System by Radin Monawir, Radin Puteri Hazimah

“…Having smart computerized system which can understand and instantly gives appropriate response to human is the utmost motive in human and computer interaction (HCI) field.It is argued either HCI is considered advance if human could not have natural and comfortable interaction like human to human interaction.Besides,despite of several studies regarding emotion detection system, current system mostly tested in laboratory environment and using mimic emotion.Realizing the current system research lack of real life or genuine emotion input,this research work comes up with the idea of developing a system that able to recognize human emotion through facial expression.Therefore,the aims of this study are threefold which are to enhance the algorithm to detect spontaneous emotion,to develop spontaneous facial expression database and to verify the algorithm performance.This project used Matlab programming language,specifically Viola Jones method for features tracking and extraction,then pattern matching for emotion classification purpose.Mouth feature is used as main features to identify the emotion of the expression.For verification purpose,the mimic and spontaneous database which are obtained from internet,open source database or novel (own) developed databases are used.Basically,the performance of the system is indicated by emotion detection rate and average execution time.At the end of this study,it is found that this system is suitable for recognizing spontaneous facial expression (63.28%) compared to posed facial expression (51.46%).The verification even better for positive emotion with 71.02% detection rate compared to 48.09% for negative emotion detection rate.Finally,overall detection rate of 61.20% is considered good since this system can execute result within 3s and use spontaneous input data which known as highly susceptible to noise.…”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Image Copy-Move Forgery Detection Algorithms Based on Spatial Feature Domain by Ahmed I.T., Hammad B.T., Jamil N.

Designing an integrated AIOT system for tracking class attendance by Kuak, Xuan Ren

“…For face detection the system uses a YOLO (You Only Look Once) algorithm, which allows quick and efficient recognition of student faces in the classroom context. …”
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Analysis of watermarking techniques in video by Shojanazeri, Hamid, Wan Adnan, Wan Azizun, Syed Ahmad Abdul Rahman, Sharifah Mumtazah, Saripan, M. Iqbal

“…Thus, research in copyright protection mechanisms, where one of which includes digital watermarking has been receiving an increasing interest from scientists especially in designing a seamless algorithm for effective implementation. Basically digital watermarking involves embedding secret symbols known as watermarks within video data which can be used later for copyright detection purposes. …”
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Optimization of Motion Compensated Block-Based DCT Video Compression for Software Implementation by Chen, Soong Der

“…This thesis focuses on ways to improve the existing solutions in the algorithmic and implementation aspects. For the algorithmic aspect, the basic principles of motion compensated DCT block-based compression scheme was studied. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Digital forensic investigation reduction model (DIFReM) for Windows 10 OS by Shayau, Yazid Haruna

“…By putting a very few files (12) in such large dataset, we made it more difficult to detect but the tool detected all modified files, added files, deleted files with modified file header, files with changed extension and also files with failed hash verification – this represented a 100% detection rate. …”
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Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

“…In the experiment, we study the effect of introducing the outlier detection in RAN-LSH. As a result, by introducing the outlier detection, we confirm that the detection accuracy is enhanced on 377$ 3(53867$.$$1781.8781$0,1$+ average over the testing period. …”
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