A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection

How do we learn an object detector that is invariant to occlusions and deformations? Our current solution is to use a data-driven strategy -- collect large-scale datasets which have object instances under different conditions. The hope is that the final classifier can use these examples to learn invariances. But is it really possible to see all the occlusions in a dataset? We argue that like categories, occlusions and object deformations also follow a long-tail. Some occlusions and deformations are so rare that they hardly happen; yet we want to learn a model invariant to such occurrences. In this paper, we propose an alternative solution. We propose to learn an adversarial network that generates examples with occlusions and deformations. The goal of the adversary is to generate examples that are difficult for the object detector to classify. In our framework both the original detector and adversary are learned in a joint manner. Our experimental results indicate a 2.3% mAP boost on VOC07 and a 2.6% mAP boost on VOC2012 object detection challenge compared to the Fast-RCNN pipeline. We also release the code for this paper.Comment: CVPR 2017 Camera Read

HEMOGLOBIN A1C IMPROVEMENTS AND BETTER DIABETES-SPECIFIC QUALITY OF LIFE AMONG PARTICIPANTS COMPLETING DIABETES SELF-MANAGEMENT PROGRAMS: A NESTED COHORT STUDY

Background: Numerous primary care innovations emphasize patient-centered processes of care. Within the context of these innovations, greater understanding is needed of the relationship between improvements in clinical endpoints and patient-centered outcomes. To address this gap, we evaluated the association between glycosylated hemoglobin (HbA1c) and diabetes-specific quality of life among patients completing diabetes self-management programs. Methods: We conducted a retrospective cohort study nested within a randomized comparative effectiveness trial of diabetes self-management interventions in 75 diabetic patients. Multiple linear regression models were developed to examine the relationship between change in HbA1c from baseline to one-year follow-up and Diabetes-39 (a diabetes-specific quality of life measure) at one year. Results: HbA1c levels improved for the overall cohort from baseline to one-year follow-up (t (74) = 3.09, p = .0029). One-year follow up HbA1c was correlated with worse overall quality of life (r = 0.33, p = 0.004). Improvements in HbA1c from baseline to one-year follow-up were associated with greater D-39 diabetes control (β = 0.23, p = .04) and D-39 sexual functioning (β = 0.25, p = .03) quality of life subscales. Conclusions: Improvements in HbA1c among participants completing a diabetes self-management program were associated with better diabetes-specific quality of life. Innovations in primary care that engage patients in self-management and improve clinical biomarkers, such as HbA1c, may also be associated with better quality of life, a key outcome from the patient perspective

Elliptic fibrations on a generic Jacobian Kummer surface

We describe all the elliptic fibrations with section on the Kummer surface X of the Jacobian of a very general curve C of genus 2 over an algebraically closed field of characteristic 0, modulo the automorphism group of X and the symmetric group on the Weierstrass points of C. In particular, we compute elliptic parameters and Weierstrass equations for the 25 different fibrations and analyze the reducible fibers and Mordell-Weil lattices. This answers completely a question posed by Kuwata and Shioda in 2008.Comment: 47 pages, 5 figures. Final versio