✍️✍️ Article: "𝗘𝘅𝗽𝗹𝗼𝗿𝗶𝗻𝗴 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗖𝗡𝗡 𝗮𝗻𝗱 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗿-𝗕𝗮𝘀𝗲𝗱 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲𝘀 𝗳𝗼𝗿 𝗢𝗿𝗶𝗲𝗻𝘁𝗲𝗱 𝗦𝗺𝗮𝗹𝗹 𝗢𝗯𝗷𝗲𝗰𝘁 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 𝗶𝗻 𝗔𝗲𝗿𝗶𝗮𝗹 𝗜𝗺𝗮𝗴𝗲𝗿𝘆"
👨💻👩💻 STUDENTS:
• Nguyen Xuan Quang - KTPM2022 - Co-author
• Le Toan - KTPM2022 - Co-author
• Tran Nguyen Chi Huy - KTPM2022 - Co-author
• Nguyen Vu Binh - KTPM2022 - Co-author
👨💼👩💼 Supervisor:
• Dr. Nguyen Tan Tran Minh Khang
Summary:
Research paper This paper evaluates the Oriented RepPoints method – a technique for detecting small objects with arbitrary orientations in overhead images. The paper experiments with various network architectures such as ResNet, ConvNeXt, and PVT, in which Simple models like ResNet-50 and ConvNeXt show better results in detecting small and oriented objects. The paper also points out some challenges like objects with similar shapes and limited training data, which provides better insights into network architecture choices in real-world applications.
"We would like to sincerely thank the Faculty of Software Engineering, the Multimedia Communication Laboratory and the UIT-Together research group for creating conditions that helped us to research and complete this article."
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Journal of Computing and Information Technology is a Q4 ranked Journal at Scimago, Scopus category
