April 15, 2024, 4:45 a.m. | Konlavach Mengsuwan, Juan Camilo Rivera Palacio, Masahiro Ryo

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.08515v1 Announce Type: new
Abstract: Object counting is a popular task in deep learning applications in various domains, including agriculture. A conventional deep learning approach requires a large amount of training data, often a logistic problem in a real-world application. To address this issue, we examined how well ChatGPT (GPT4V) and a general-purpose AI (foundation model for object counting, T-Rex) can count the number of fruit bodies (coffee cherries) in 100 images. The foundation model with few-shot learning outperformed the …

abstract agriculture application applications arxiv chatgpt count cs.cv data deep learning domains eess.iv general gpt4v issue logistic object popular training training data type world

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