Results 41 to 50 of about 2,965,444 (278)
Adversarial Data Programming: Using GANs to Relax the Bottleneck of Curated Labeled Data
, 2018 Paucity of large curated hand-labeled training data for every domain-of-interest forms a major bottleneck in the deployment of machine learning models in computer vision and other fields.
Balasubramanian, Vineeth N, Pal, Arghya
core +1 more source
Automatic Labeled LiDAR Data Generation based on Precise Human Model
, 2019 Following improvements in deep neural networks, state-of-the-art networks have been proposed for human recognition using point clouds captured by LiDAR. However, the performance of these networks strongly depends on the training data.
Kim, Wonjik +3 more
core +1 more source
MdpCaps-Csl for SAR Image Target Recognition With Limited Labeled Training Data
IEEE Access, 2020 Although convolutional neural networks (CNN) have shown excellent performance in many image recognition tasks, it commonly requires a lot of labeled data, and the recognition effect is frequently unsatisfied due to the limited labeled training data.
Yuchao Hou +5 more
doaj +1 more source
Learning From Noisy Singly-labeled Data [PDF]
, 2018 Supervised learning depends on annotated examples, which are taken to be the \emph{ground truth}. But these labels often come from noisy crowdsourcing platforms, like Amazon Mechanical Turk. Practitioners typically collect multiple labels per example and
Anandkumar, Anima +2 more
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Clinical Insights Into Hypercalcemia of Malignancy in Childhood
Pediatric Blood &Cancer, EarlyView.ABSTRACT Hypercalcemia of malignancy (HCM) is a rare but life‐threatening metabolic emergency in children that occurs in less than 1% of pediatric cancer cases, with a reported incidence ranging from 0.4% to 1.0% across different studies. While it is observed in 10%–20% of adult malignancies, pediatric HCM remains relatively uncommon.
Hüseyin Anıl Korkmaz
wiley +1 more source
Semi-Supervised Learning by Augmented Distribution Alignment
, 2019 In this work, we propose a simple yet effective semi-supervised learning approach called Augmented Distribution Alignment. We reveal that an essential sampling bias exists in semi-supervised learning due to the limited number of labeled samples, which ...
Li, Wen, Van Gool, Luc, Wang, Qin
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Objective To evaluate the diagnostic yield and utility of universal paired tumor–normal multigene panel sequencing in newly diagnosed pediatric solid and central nervous system (CNS) tumor patients and to compare the detection of germline pathogenic/likely pathogenic variants (PV/LPVs) against established clinical referral criteria for cancer ...
Natalie Waligorski +9 more
wiley +1 more source
Data for analysis of mannose-6-phosphate glycans labeled with fluorescent tags
Data in Brief, 2016 Mannose-6-phosphate (M-6-P) glycan plays an important role in lysosomal targeting of most therapeutic enzymes for treatment of lysosomal storage diseases.
Ji-Yeon Kang +3 more
doaj +1 more source
Crisis social media data labeled for storm-related information and toponym usage
Data in Brief, 2020 Social media provides citizens and officials with important sources of information during times of crisis. This data article makes available labeled, storm-related social media data collected over a six-hour period during a severe storm and F1 tornado ...
Rob Grace
doaj +1 more source
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Objective To compare the efficacy and safety of roxarestat versus recombinant human erythropoietin (rhEPO) in the management of renal anemia in patients undergoing maintenance hemodialysis. Methods This was a prospective, open‐label, randomized controlled trial.
Lingling Chen, Junjie Zhu, Qiaonan Ge
wiley +1 more source