Incidence estimates for well spaced tubes

We prove analogues of the Szemer\'edi-Trotter theorem and other incidence theorems using $\delta$-tubes in place of straight lines, assuming that the $\delta$-tubes are well-spaced in a strong sense.Comment: 17 page

Group Behavior and Development: A Comparison of Farmers' Organisations in South Korea and Taiwan

This study presents a comparative analysis of farmers' organisations in Korea and Taiwan during 1950-80 in order to help us understand the role of group behavior in affecting development outcomes. It highlights the linkages between group behavior, parastatal organisational structures and economic performance. The paper examines the historical and political economy contexts that led to the creation of both countries' farmers' organisations and highlights the institutional characteristics that impacted their operational effectiveness. The study discusses elements in internal and external policies that affected group motivation and traces the implications of such differences in group behavior for bottom line performance. Though there existed many similarities in both organisational structure and operations, it is argued that differential intra-group behavioral dynamics led to differences in agricultural performance. Although, with the declining importance of agriculture, the relative importance of such organisations has declined in recent years, the study is relevant for developing countries at every stage of development.Farmers' Organizations, Korea, Taiwan, Group Behavior

Mining Discriminative Triplets of Patches for Fine-Grained Classification

Fine-grained classification involves distinguishing between similar sub-categories based on subtle differences in highly localized regions; therefore, accurate localization of discriminative regions remains a major challenge. We describe a patch-based framework to address this problem. We introduce triplets of patches with geometric constraints to improve the accuracy of patch localization, and automatically mine discriminative geometrically-constrained triplets for classification. The resulting approach only requires object bounding boxes. Its effectiveness is demonstrated using four publicly available fine-grained datasets, on which it outperforms or achieves comparable performance to the state-of-the-art in classification