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Chapter and Conference Paper
Deep Learning-Based Silicon Wafer Defect Classification: A Performance Comparison of Pretrained Networks
Semiconductor processing technology heavily relies on defect inspection to enhance yield by identifying surface defects in the manufacturing process. However, manual inspection is prone to errors and can be a ...
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Chapter and Conference Paper
Character Recognition Based on k-Nearest Neighbor, Simple Logistic Regression, and Random Forest
Characters recognition has gained significant attention in recent years within the field of artificial intelligence and computer vision as robots increasingly engage in activities that involve collecting and p...
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Chapter and Conference Paper
Deep Learning for Breast Cancer Detection from Mammograms Images
Mammograms has been widely used for early detection of breast cancer; however, radiologists are prone to error which could lead to unnecessary tests or missed treatment window. With the advancement of state-of...
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Chapter and Conference Paper
Hyperparameter Optimization of Deep Learning Model: A Case Study of COVID-19 Diagnosis
The global impact of COVID-19, which has affected over 700 million individuals, necessitates the development of automated diagnostic tools for rapid screening using clinical imaging, such as X-rays. Deep learn...
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Chapter and Conference Paper
Object Detection in Autonomous Vehicles: A Performance Analysis
Automotive manufacturers are investing in smart cars, driverless processes, and pre-collision technologies to deliver safe and fuel-efficient mobility solutions. This paper aims to develop an advanced object d...
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Chapter and Conference Paper
Wrapper-Based Feature Selection Using Sperm Swarm Optimization: A Comparative Study
Feature selection is a vital technique that enhances the quality of input datasets by reducing redundancy, noise, and inaccuracies without compromising classifier accuracy. The integration of metaheuristic sea...
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Chapter and Conference Paper
A Modified African Vultures Optimization Algorithm for Enhanced Feature Selection
Feature selection is a reliable technique for reducing redundant, noisy, or inaccurate features in raw input datasets without compromising classifier accuracy. Integrating metaheuristic search algorithms (MSAs...
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Chapter and Conference Paper
Optimization Strategies for Training Artificial Neural Network: A Case Study in Medical Classification
Backpropagation (BP) is a widely embraced method for training artificial neural networks (ANNs) in classification and regression tasks. However, its efficacy diminishes when confronted with complex problems du...
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Chapter and Conference Paper
X-Ray Baggage Object Detection Using Neural Networks Approach for Safety Purpose
Airport security a matter of urgent attention and this calls for measures to ensure that all baggage that move within the airport contain non-harmful objects that may people at the airport in danger. Over the ...
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Chapter and Conference Paper
A Real-Time Social Distancing and Face Mask Detection System Using Deep Learning
It has been more than two years since the transmission of COVID-19 virus has affected the public health globally. Due to its natural characteristic, the virus is very likely to undergo mutation over time and c...
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Chapter and Conference Paper
Detection of Lead with IoT Water Monitoring System Using Microstrip Antenna-Based Sensor
This paper presents a microstrip antenna-based sensor for detecting lead in water. The proposed antenna consists of a simple rectangular patch with inset feeding with an overall size of 50 mm × 45 mm. CST Stud...
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Chapter and Conference Paper
Flow Direction Algorithm for Feature Selection
Feature selection is a method used to decrease the number of features by removing unwanted, noisy and inconsistent data while maintaining classification accuracy. Most researchers have focused on using metaheu...
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Chapter and Conference Paper
Optimized Machine Learning Model with Modified Particle Swarm Optimization for Data Classification
Metaheuristic search algorithms (MSAs) receive increasing popularity in recent year due to its excellent capability of solving complex real-world optimization problems without depending on gradient information...
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Chapter and Conference Paper
An Optimized Deep Learning Model for Automatic Diagnosis of COVID-19 Using Chest X-Ray Images
COVID-19 has caused havoc throughout the world in the last two years by infecting over 455 million people. Development of automatic diagnosis software tools for rapid screening of COVID-19 via clinical imaging...
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Chapter and Conference Paper
Feature Selection of Medical Dataset Using African Vultures Optimization Algorithm
Feature selection is one of the popular techniques used to reduce the number of features by eliminating noisy, unreliable, and unnecessary data without affecting the classification accuracy. Metaheuristic algo...
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Chapter and Conference Paper
Training Feedforward Neural Networks Using Arithmetic Optimization Algorithm for Medical Classification
Feedfoward neural network (FNN) is popular machine learning technique widely implemented for image classification, data clustering, object recognition, etc. due to its outstanding capability in processing data...
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Chapter and Conference Paper
Flexible Wearable Microstrip Antenna with DGS and Shorting Post for WBAN Application
A novel flexible microstrip patch antenna with multiple notches, Defected Ground Structure (DGS) and Shorting Post technique (SP) is presented to enhance the antenna performance. The proposed antenna design co...
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Chapter and Conference Paper
Simulation Studies on Bimorph and Unimorph PZT Piezoelectric Transducer for Energy Harvesting Application
Various studies have shown that energy harvesting using piezoelectric material is a promising path opened to more opportunities for future applications. This study is mainly focused on the comparison between b...
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Chapter and Conference Paper
Tomato Leaf Health Monitoring System with SSD and MobileNet
Recent developments in Deep Learning have allowed researchers to propose fast and accurate computer-based methods that have been applied to detect plant diseases. However, most of the methods typically focus o...
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Chapter and Conference Paper
Computer-Vision-Based Integrated Circuit Recognition Using Deep Learning
Computer vision technology is widely implemented in electronic manufacturing industry to detect the defects on printed circuit board (PCB). However, the wrong attachment of electronic components is a notable i...
