Search Results - (( lesion classification technique algorithm ) OR ( java application interface algorithm ))
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Automated Segmentation And Classification Technique For Brain Stroke
Published 2019“…This study proposes a segmentation and classification technique to detect brain stroke lesions based on diffusion-weighted imaging (DWI). …”
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Novel techniques for enhancement and segmentation of acne vulgaris lesions
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Automated diagnosis of focal liver lesions using bidirectional empirical mode decomposition features
Published 2018“…The accuracy, sensitivity, and specificity of lesion classification were 92.95%, 90.80%, and 97.44%, respectively. …”
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An efficient AdaBoost algorithm for enhancing skin cancer detection and classification
Published 2024“…The novelty lies in the combination of these techniques to develop a robust and accurate system for skin cancer classification. …”
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Identifying melanoma characteristics using directional imaging algorithm and convolutional neural network on dermoscopic images / Mohammad Asaduzzaman Rasel
Published 2024“…This research is divided into two phases – 1) Feature Engineering phase explains skin conditions based on lesion segmentation and different dermoscopic feature extraction, while 2) Classification phase detects Melanoma. …”
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Thesis -
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Real-time algorithmic music composition application.
Published 2022“…In addition, the system also utilises JavaFx and jFugue for its graphical user interface and music programming respectively. …”
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Final Year Project / Dissertation / Thesis -
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Application-Programming Interface (API) for Song Recognition Systems
Published 2024“…In addition the implementation is done by algorithm using Java’s programming language, executed through an application developed in the Android operating system. …”
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Development of a CAD system for stroke diagnosis using machine learning on DWI-MRI images
Published 2025“…A hybrid segmentation technique, fuzzy c-means with active contour (FCMAC), is proposed to enhance lesion localization accuracy. …”
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Visdom: Smart guide robot for visually impaired people
Published 2025“…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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Final Year Project / Dissertation / Thesis -
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Development Of Machine Learning User Interface For Pump Diagnostics
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Monograph -
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Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework
Published 2004“…A design proposal was outlined to provide an adaptive client/server approach to stream audio contents using Real-Time Transport Protocol (RTP) involving architecture based on the Java Media Framework (JMF) Application Programmable Interfaces (API).RTP protocol is the Internet-standard protocol for the transport of real-time data, including audio and video and can be implemented by using Java Media Framework (JMF). …”
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Thesis -
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Movie recommendation system / Najwa Syamimie Hasnu
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The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer
Published 2023“…Most of the techniques found in this survey address these two problems. …”
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Implementation of (AES) Advanced Encryption Standard algorithm in communication application
Published 2014“…The concept of ABS algorithm was firstly studied, including the definition, historical background, and a brief comparison was made between the ABS algorithm with other types of algorithm. …”
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Undergraduates Project Papers -
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SANAsms: Secure short messaging system for secure GSM mobile communication
Published 2008“…The application is designed to satisfy the user friendly interfaces and intent to be used by the end user without having the advanced knowledge in mobile security. …”
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Design Of Robot Motion Planning Algorithm For Wall Following Robot
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Monograph -
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Computer-assisted pterygium screening system: a review
Published 2022“…During the early stage of automated pterygium screening system development, conventional machine learning techniques such as support vector machines and artificial neural networks are the de facto algorithms to detect the presence of pterygium tissues. …”
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