The research project aims to develop an AI-driven method for optimizing the selection of applicants in a competitive recruitment process. The study involves data analysis, model development, and performance evaluation to enhance the efficiency and effectiveness of applicant selection procedures, with the goal of presenting the findings at a prestigious industry conference.
The study investigates deep learning techniques for the classification of coral species, leveraging a range of advanced models for accurate classification. The paper discusses the model architecture, dataset preparation, training strategies, and performance evaluation methods.
The research paper focuses on the design, implementation, and performance evaluation of Raspberry Pi-based computing prototypes for diverse practical applications. The study explores various use cases, testing methodologies, and performance benchmarks to optimize prototype performance.
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CS & MATH @ GVSU | SWE/DE @ GVSU Applied Computing Institute.
