Search Results - (( (emotion OR motion) detection method algorithm ) OR ( storage optimization based algorithm ))

Analysis of Motion Detection of Breast Tumor Based on Tissue Elasticity From B Mode Ultrasound Images Using Gradient Method Optical Flow Algorithm by Shuib, FMM, Abdulrahim, K, Zulkifli, Z, Marinah Othman

Web Camera Application For Motion Detection by Koay, Su Yeong

“…The new method to detect motion is "vision motion detection". …”
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Analysis of motion detection of breast tumor based on tissue elasticity from B mode ultrasound images using gradient method optical flow algorithm by Shuib F.M.M., Othman, M., Abdul Rahim, K., Zulkifli Z.

Subjects:

Optimization algorithms for energy storage integrated microgrid performance enhancement by Roslan M.F., Hannan M.A., Ker P.J., Muttaqi K.M., Mahlia T.M.I.

Backtracking Search Algorithm Based Fuzzy Charging-Discharging Controller for Battery Storage System in Microgrid Applications by Faisal M., Hannan M.A., Ker P.J., Uddin M.N.

Pumped-storage scheduling using particle swarm optimization / Amirul Asraf Razali by Razali, Amirul Asraf

“…This thesis presents the solution algorithm based on the particle swarm optimization (PSO) for solving the pumped-storage (P/S) scheduling problem. …”
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Emotion Detection Based on EEG Signal by Mohamad Nasaruddin, Noradila

“…Thus, this project aimed to study the emotion detection through EEG signal and proposed the right algorithm to process the signal. …”
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Vision-based flame analysis using motion and Edge Detection by Razmi, Suzilawati Mohd, Saad, Nordin, Asirvadam, Vijanth Sagayan

“…This paper stresses on the flame detection algorithm. The results show that detection of flame using motion amp; shape features can be achieved by using Background Subtraction and Edge Detection approach.…”
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MotionSure: a cloud-based algorithm for detection of injected object in data in motion by Islam, Thouhedul, Olanrewaju, Rashidah Funke, Khalifa, Othman Omran

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Vision-based flame detection: Motion detection amp; fire analysis by Mohd Razmi, S., Saad , Nordin, Asirvadam , Vijanth Sagayan

“…It is very crucial to develop a reliable method to detect an occurrence of fire. In this paper, vision-based flame detection using motion detection algorithm is discussed. …”
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Development of a personified face emotion recognition technique using fitness function by Muthukaruppan, Karthigayan, Mohd Rizon, Mohamed Juhari, Ramachandran, Nagarajan, Masanori, Sugisaka, Sazali, Yaacob, Mohd Rozailan, Mamat, Hazry, Desa

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Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications by Hannan M.A., Faisal M., Jern Ker P., Begum R.A., Dong Z.Y., Zhang C.

Optimizing Cloud Storage Costs: Introducing the Pre-Evaluation-Based Cost Optimization (PECSCO) Mechanism by Alomari M.F., Mahmoud M.A., Gharaei N., Rasool S.M., Hasan R.A.

“…Nonetheless, cloud service providers impose fees on users based on the volume of data transmitted to and from cloud storage, resulting in elevated storage costs. …”

Depth frame loss concealment for wireless transmission utilising motion detection information by Ranjbari, Mohamadreza

“…The feasibility and performance of the proposed method based on motion detection error concealment is evaluated analytically by considering different packet and frame loss rates. …”
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A real-time vision-based touchless interaction of virtual heart using integration of motion gesture interaction methods by Ng, Ing Kye

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Investigation of block matching algorithm for video coding by Faizul Hadi Mohamad Jamil

“…The temporal model deals with motion estimation (ME) and motion compensation (MC) algorithm with the matching technique called “Block Matching Algorithm” (BMA) to produce the next encoded video frame with motion vector. …”
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Motion detection using Horn-Schunck optical flow by Wan Nur Azhani, W. Samsudin, Kamarul Hawari, Ghazali

“…This system is design to detect motion in a crowd using one of the optical flow algorithms, Horn-Schunck method. …”
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An evaluation of optical flow algorithms for crowd analytics in surveillance system by Kajo, I., Malik, A.S., Kamel, N.

“…This paper presents an overview of the optical flow methods that used mainly for pedestrian and crowd motion detection. …”
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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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GPSO versus GA in facial emotion detection by Bashir, Mohammed Ghandi, Ramachandran, Nagarajan, Prof. Dr., Sazali, Yaacob, Prof. Dr., Hazry, Desa, Assoc. Prof. Dr.

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