Surficial geologic map of the Des Moines Lobe of Iowa, Phase 5: Polk County

https://ir.uiowa.edu/igs_ofm/1030/thumbnail.jp

Label Scarcity in Computer Vision: From Long Tail to Zero-shot

In the era of big data, we have access to various sources of potentially unlimited data, but collecting labels for those data is still very costly for computer vision. For example, object detection requires the images to be annotated with labels and bounding boxes for all objects, and instance segmentation requires pixel level annotation of images. Given the limited budget and the non-uniform distribution of real world data, the available labels we have usually follows a long tail distribution, where some frequent classes have a lot of annotations while rare classes have very few labels. With the rapid growth of the Internet, people create new content and concepts almost every day, and it is hard for machines to recognize and classify such novel content, which gives rise to another kind of label scarcity named zero-shot recognition, where we want to train models to recognize new classes that they never see during training. In this work, we study the two types of label scarcity (i.e., long tail distribution of classes and novel classes without annotations) in different applications. On one hand, we study dealing with long tail distribution in scene graph parsing, which requires the model to not only detect objects in the input images but also predict the relations between those objects. We propose a general framework that can be applied to and improve many existing models, by decomposing the problem into classification and ranking sub-problems. On the other hand, to deal with label scarcity caused by novel classes with no annotations, we design generative models as well as utilize external knowledge from text to solve different zero-shot recognition problems in image classification. Specifically, we propose a unified framework for single label zero-shot recognition with generative adversarial networks, and use graph convolutional networks to bridge the gap between seen and unseen classes for multi-label zero-shot image recognition. Additionally, we propose a translational embedding model that recognize new attribute-object compositions. All the works mentioned above use open-source public datasets like ImageNet, MS-COCO, NUS-WIDE and CUB

MOESM1 of Effects of extended stance time on a powered knee prosthesis and gait symmetry on the lateral control of balance during walking in individuals with unilateral amputation

Additional file 1: Table S1. ANOVA results with the inclusion/exclusion of each identified outlier trial. In total, we identified five outlier trials in five outcome measures (listed below). However, the inclusion/exclusion of these identified outlier trials did not affect the significance of our results (below, significance level 0.01). Therefore, we only excluded two outlier trials that were outliers in multiple responses (i.e. one outlier trial in stride time and stance time, one outlier trial in swing time and double support time)

Intramolecular Alkyne Carbomercuration by Allylic Silanes: A New Carbon−Carbon Bond-Forming Reaction

Intramolecular Alkyne Carbomercuration by Allylic Silanes:  A New Carbon−Carbon Bond-Forming Reactio

Regiodivergent Electrophotocatalytic Aminooxygenation of Aryl Olefins

A method for the regiodivergent aminooxygenation of aryl olefins under electrophotocatalytic conditions is described. The procedure employs a trisaminocyclopropenium (TAC) ion catalyst with visible light irradiation under a controlled electrochemical potential to convert aryl olefins to the corresponding oxazolines with high chemo- and diastereoselectivity. With the judicious choice between two inexpensive and abundant reagents, namely water and urethane, either 2-amino-1-ol or 1-amino-2-ol derivatives could be prepared from the same substrate. This method is amenable to multigram synthesis of the oxazoline products with low catalyst loadings

The Number of (A) AB and (B) TF Subjects whose Subjective Feedback (S) and Quantified Balance Index (O) Reported Gait Instability when the Prosthesis Mode Switched at Different Timings.

<p>White area indicates none of the subjects showed gait instability, evaluated either subjectively (S) or objectively (O).</p

Model Studies Support Pyrrolylation of the Topaquinone Cofactor To Explain Inactivation of Bovine Plasma Amine Oxidase by 3-Pyrrolines. Unusual Processing of a Secondary Amine

Model Studies Support Pyrrolylation of the Topaquinone Cofactor To Explain Inactivation of Bovine Plasma Amine Oxidase by 3-Pyrrolines. Unusual Processing of a Secondary Amin

Forest plot for meta-analysis comparing risk of stroke in HCV infected patients compared to that in non-infected controls.

<p>Four studies reporting ORs and RR were included. Adjusted ORs from included studies and the pooled OR was shown. Dimension of shaded OR for individual studies is proportional to their total weight in calculation of the pooled estimator. </p

Change of Mechanical Work on TF Subjects in Each Gait Phase when the Prosthesis Control Mode Was Switched from Level-ground Walking to Ramp Ascent (W→RA) at Timings that Were Reported Unstable (IDS_1, SS_1, TDS_2, SWF_2, and SWE_2).

<p><u>Note</u>: The values were averaged across two TF subjects.</p><p>“*” indicated that the change of mechanical work was out of the tolerable range that was observed in the previous study.</p><p>“-” meant that the mechanical work change was not calculated. The unit of mechanical work change was J/Kg.</p><p>Change of Mechanical Work on TF Subjects in Each Gait Phase when the Prosthesis Control Mode Was Switched from Level-ground Walking to Ramp Ascent (W→RA) at Timings that Were Reported Unstable (IDS_1, SS_1, TDS_2, SWF_2, and SWE_2).</p