Legal and social dynamics of eBook lending in Australia’s public libraries. Legal and social dynamics of eBook lending in Australia’s public libraries. This project aims to develop an evidence base of quantitative and qualitative data about how eBooks are used in libraries. EBooks have tremendous beneficial potential, particularly for Australians in remote areas and those with impaired mobility or vision. However, libraries’ rights to acquire and lend them are more restricted than for physical b ....Legal and social dynamics of eBook lending in Australia’s public libraries. Legal and social dynamics of eBook lending in Australia’s public libraries. This project aims to develop an evidence base of quantitative and qualitative data about how eBooks are used in libraries. EBooks have tremendous beneficial potential, particularly for Australians in remote areas and those with impaired mobility or vision. However, libraries’ rights to acquire and lend them are more restricted than for physical books. Libraries and legal, social and data science researchers will investigate eBook lending practices and understand their social impacts. The project will identify ways of reforming policy, law, and practice to help libraries fulfil their public interest missions. This project is expected to enable libraries to extract more value from existing public investments.Read moreRead less
Single model irregular-region retrieval for rapid plant disease detection. This project aims to study the major technical barrier in plant disease image retrieval to build a pervasive rapid plant disease identification system. The techniques are designed to function on one or very few sample images, thus enabling on-line in field disease identification linked to authoritative plant disease image libraries. The success of this project will not only make significant contributions to fundamental th ....Single model irregular-region retrieval for rapid plant disease detection. This project aims to study the major technical barrier in plant disease image retrieval to build a pervasive rapid plant disease identification system. The techniques are designed to function on one or very few sample images, thus enabling on-line in field disease identification linked to authoritative plant disease image libraries. The success of this project will not only make significant contributions to fundamental theory in single model image retrieval, but also create a revolution in plant disease early detection for effective and efficient crop protection.Read moreRead less