For many practical problems and applications, it is not feasible to create a vast accurately labeled dataset, which restricts the application of deep learning in areas. Semi-supervised algorithms intend improve performance by also leveraging unlabeled data. This very valuable for 2D-pose estimation task where data labeling requires substantial time subject noise. work aims investigate if semi-s...

Weight information is important in cattle breeding because it can measure animal growth and be used to calculate the appropriate amount of daily feed. To estimate weight, we developed an image-based method that does not stress requires no manual labor. From a 2D image, mask was obtained by segmenting background, weights were estimated using deep neural network with residual connections extracti...

OBJECTIVE The image quality for gastrointestinal bleeding studies depends on the efficiency of red blood cell labeling. The in vitro technique has been used widely because of its high labeling efficiency. New data for the modified in vivo/in vitro method are lacking. This study reports on the high labeling efficiency that can be obtained with the modified in vivo/in vitro method and the pitfall...

I read with great interest the recent article by Bonito et al. [1] in a recent issue of your esteemed journal. The article is highly thought provoking. Geminin is rapidly emerging as a significant marker and prognostic indicator in a number of systemic malignancies besides breast malignancies. A worse clinical outcome and correspondingly a lower relapse-free survival rate are seen in salivary g...

The objective of this study is to develop a patch-based labeling method that cooperates with a label fusion using non-rigid registrations. We present a novel patch-based label fusion method, whose selected patches and their weights are calculated from a combination of similarity measures between patches using intensity-based distances and labeling-based distances, where a previous labeling of t...

OBJECTIVES We sought to elucidate the 3-dimensional position and quantify the lower motor neurons (LMNs) of the recurrent laryngeal nerve (RLN) and the superior laryngeal nerve (SLN) in a rat model. Quantification and mapping of these neurons will enhance the usefulness of the rat model in the study of reinnervation following trauma to these nerves. METHODS Female Sprague-Dawley rats underwen...

Two experiments explore children's spontaneous labeling of novel objects as a method to study early lexical access. The experiments also provide new evidence on children's attention to object shape when labeling objects. In Experiment 1, the spontaneous productions of 21 23- to 28-month-olds (mean 26;28) shown a set of novel, unnamed objects were analyzed both in terms of the specific words sai...

Crowdsourcing label generation has been a crucial component for many real-world machine learning applications. In this paper, we provide finite-sample exponential bounds on the error rate (in probability and in expectation) of hyperplane binary labeling rules for the Dawid-Skene (and Symmetric DawidSkene ) crowdsourcing model. The bounds can be applied to analyze many commonly used prediction m...