Reference no: EM133626697

Task Background:

This assignment is titled: "Enhancing Data Information Management for Improved Traffic Light Classification". In the realm of data information management and computer vision, there is a pressing need for robust systems to classify used traffic lights for road safety and infrastructure maintenance. This assignment revolves around the development of AI/ML/DL models for accurate traffic light classification, with a significant emphasis on optimizing data information management.

Assignment Tasks:

Dataset: Start by assembling a comprehensive dataset for training, validation, and testing of your traffic light classification models. The dataset should comprise images of traffic lights captured at various resolutions and under diverse lighting conditions. Provide insights into the data collection methodology and strategies for dataset quality and balance.

Algorithm Review: Perform an exhaustive review of existing AI algorithms and techniques utilized for traffic light classification in computer vision applications. Analyze their strengths, weaknesses, and areas where improvements can be made. Identify specific aspects in which your new model is designed to excel compared to existing methods.

Model Innovation: Leverage your understanding of existing algorithms to design an innovative AI/ML/DL model optimized for traffic light classification. Describe how your model surpasses existing methods, emphasizing advantages such as enhanced accuracy, real-time processing, or adaptability to variable lighting and weather conditions. Elaborate on any novel techniques or architectural enhancements incorporated into your model.

Tool Selection: Choose suitable Python libraries and tools for effective image extraction and classification. Explain your rationale for these selections and how these tools contribute to data information management optimization.

This assignment is structured to encourage students to explore the intricacies of data information management within the context of computer vision. It promotes innovation in AI/ML/DL model design for traffic light classification while emphasizing the crucial role of dataset construction and management. It seeks to motivate students to develop a light-weight CNN grayscale traffic light image classifier that can achieve an accuracy as good as transfer learning applied to a pre-trained color image classifier model. Upon completing this assignment, students should be proficient in the field of computer vision and capable of applying these skills to real-world challenges with cutting-edge solutions.