Titlebook: Intelligent Manufacturing and Mechatronics; Proceedings of SIMM Roshaliza Hamidon,Muhammad Syahril Bahari,Zailani Conference proceedings

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Performance of Extreme Learning Machinepular classification algorithms is compared, the Extreme Learning Machine (ELM) and k-Nearest Neighbors (KNN) classifiers. ELM is a single hidden layer feedforward neural network that uses random weights for quick training and good accuracy. A nonparametric classification technique called KNN, on th

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Oil Palm Fresh Fruit Branch Ripeness Detection Using YOLOV6 Algorithmthe Malaysian economy. Currently, oil palm fresh fruit branches (FFBs) are harvested by human graders at oil palm plantations based on the fruit surface colour and the number of loose fruits on the ground as a measure of the ripeness level. However, solely relying on human graders would result in mi

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Performance Comparisons of GNB, RBF-SVM and NN for Stress Levels Classification Using Discrete Wavelausing stress to accumulate. Early recognition of stress has become imperative to avoid long-term exposure leading to mental health disorders. The application of electroencephalography (EEG) facilitates the need for stress signal identification. By observing the brain wave pattern, stress-related fe

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Conference proceedings 2024logy, mechanical and design, instrumentation and control systems, modelling and simulation, industrial engineering, material, and processing and mechatronics and robotics, the book is a valuable resource for readers wishing to embrace the new era of technological transformation..

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Additive Manufacturing: Stringing and Warping Detection Using MobileNet-SSDa neural network model, image pre-processing, hyperparameter tuning, and model training and validation. The accuracy of the proposed model was evaluated, and the results achieved a mean average precision (mAP) of 28%. The proposed approach is effective in detecting defects compared to ResNet-SSD with mAP 21.4%.

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