Nurul Amirah Mashudi

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Affiliation

Faculty of Artificial Intelligence, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia

Topic

Deep Learning,Machine Learning,Random Forest,Support Vector Machine,Computation Time,Convolutional Neural Network,Decision Tree,F1 Score,Generative Adversarial Networks,Graphics Processing Unit,Machine Learning Methods,Neural Network,Precision And Recall,10-fold Cross-validation,3-fold Cross-validation,5-fold Cross-validation,Accurate Results,Artificial Intelligence Technology,Artificial Neural Network,Artificial Neural Network Method,Attention Mechanism,Autoregressive Integrated Moving Average Model,Average Recall,Batch Size,Benign Tumors,Bidirectional Long Short-term Memory,Bounding Box,Breast Cancer,Breast Cancer Dataset,Classification Accuracy,Classification Of Breast Cancer,Classification Of Diseases,Classification Performance,Computer Vision,Conditional Generative Adversarial Network,Convolutional Layers,Convolutional Network,Corn Leaf,Crop Yield,Cybersecurity,Data Augmentation,Data Mining,Data Protection,Deep Learning Approaches,Deep Learning Architectures,Deep Learning Models,Denial Of Service,Dependability,Depthwise Separable Convolution,Detection System,

Biography

Nurul Amirah Mashudi (Graduate Student Member, IEEE) received the Diploma degree in computer science from the International Islamic College, Kuala Lumpur, and the B.Sc. degree in graphics and multimedia software and the M.Sc. degree in systems engineering from Universiti Teknologi Malaysia (UTM), Kuala Lumpur, Johor Bahru. Currently, she is working as an Information Technology (IT) Lecturer at City University Malaysia, Johor Bahru Campus. Her current research interests include image recognition, pattern recognition, image processing, image analysis, and machine learning applications.