Developed and trained a Convolutional Neural Network (CNN) based on the AlexNet architecture for real-time detection of potholes in asphalt roads, achieving 92.15% accuracy, 91.38% sensitivity, and an F-score of 96.52%. Optimized the model using high-performance GPUs for deployment in real-time systems.
May 1, 2024
Led a team in the design and implementation of a hybrid CNN and Waterwheel Plant Algorithm (WWPA) to detect and track vehicles in global traffic data, achieving a model accuracy of 97.28%.'
Jan 1, 2024
Applied various deep learning architectures to predict and analyze traffic patterns in urban environments, with AlexNet emerging as the best-performing model, achieving an accuracy of 93.18%.
Dec 1, 2023
Spearheaded the development of an oil spill detection system using Artificial Neural Networks (ANN), achieving 96.88% accuracy by classifying ocean satellite images.
Apr 1, 2023
Built a deep learning model using MobileNetV2 to detect face masks, a crucial tool for public safety during the COVID-19 pandemic. Achieved a 97.71% accuracy on the test dataset, demonstrating the model’s robustness and efficiency under varying conditions.
Mar 15, 2023
Led a team to implement the Greylag Goose Optimization (GGO) algorithm for enhancing a Multilayer Perceptron (MLP) Regressor, reducing Mean Squared Error (MSE) significantly.
Mar 1, 2023
Collaborated on developing a robust student performance prediction model by integrating the Binary Waterwheel Plant Algorithm (bWWPA) for feature selection, achieving a notable reduction in MSE.
Feb 1, 2023
Conducted exploratory data analysis (EDA) on a large retail dataset to identify key sales patterns, trends, and product performance metrics. Utilized Python libraries like Pandas, NumPy, Matplotlib, and Seaborn for comprehensive data visualization and insight generation.
Jan 1, 2023