Results 81 to 90 of about 254,373 (189)

Facial Component-Landmark Detection With Weakly-Supervised LR-CNN

IEEE Access, 2019
In this paper, we propose a weakly supervised landmark-region-based convolutional neural network (LR-CNN) framework to detect facial component and landmark simultaneously.
Ruiheng Zhang, Chengpo Mu, Min Xu, Lixin Xu, Xiaofeng Xu   +4 more
doaj   +1 more source

From domain-landmark graph learning to problem-landmark graph generation

Landmarks have long played a pivotal role in automated planning, serving as crucial elements for improving the planning algorithms. The main limitation of classical landmark extraction methods is their sensitivity to specific planning tasks. This results in landmarks fully tailored to individual instances, thereby limiting their applicability across ...
Pérez-Corral, Cristian, Garrido, Antonio, Sebastia, Laura   +2 more
openaire   +2 more sources

Geomagnetic Field Based Indoor Landmark Classification Using Deep Learning

IEEE Access, 2019
The unstable nature of radio frequency signals and the need for external infrastructure inside buildings have limited the use of positioning techniques, such as Wi-Fi and Bluetooth fingerprinting.
Bimal Bhattarai, Rohan Kumar Yadav, Hui-Seon Gang, Jae-Young Pyun   +3 more
doaj   +1 more source

Gray-Edge-HOG feature based cascaded learning for facial landmark detection

MATEC Web of Conferences, 2018
Compared with the traditional statistical models, such as the active shape model and the active appearance model, the facial feature point localization method based on deep learning has improved in accuracy and speed, but there still exist some problems.
Zhang Wenhui, Wang Wentong, Zhao Shuang, Sun Bin   +3 more
doaj   +1 more source

Relational Reasoning Network (RRN) for Anatomical Landmarking

, 2019
Accurately identifying anatomical landmarks is a crucial step in deformation analysis and surgical planning for craniomaxillofacial (CMF) bones. Available methods require segmentation of the object of interest for precise landmarking.
Bagci, Ulas, Han, Wade W., Lee, Janice S., Liberton, Denise K., McIntosh, Mary, Sincan, Murat, Torosdagli, Neslisah, Verma, Payal   +7 more
core  

Landmark Detection Using Machine Learning

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
As smartphones and mobile data become more prevalent in modern society, the possibilities for them to interact with the physical world also grow exponentially. Technologies such as Oculus Rift and Google Glass are attempting to bridge the gap between the virtual and the physical, and as enhancements in computer speed and image processing are made, the ...
openaire   +1 more source

Automated Bony Landmark Detection on Foot Radiographs: Facilitating Linear and Angular Measurements

Foot & Ankle Orthopaedics
Research Type: Level 3 - Retrospective cohort study, Case-control study, Meta-analysis of Level 3 studies Introduction/Purpose: Accurate assessment of foot alignment on radiographs relies on precise identification of key bony landmarks. Manual annotation
Atta Taseh MD, Junjie Li MS, Shrestha Mishra, Carl Rai MD, Ronit Avadhuta, Matthias Peiffer MD, PhD, Bedri Karaismailoglu MD, FEBOT, PhDc, Gregory Waryasz MD, Lorena Bejarano-Pineda MD, Christopher Miller MD, Soheil Ashkani-Esfahani MD, MPH, PhDc   +10 more
doaj   +1 more source

Learning Landmarks by Exploiting Social Media

, 2010
This paper introduces methods for automatic annotation of landmark photographs via learning textual tags and visual features of landmarks from landmark photographs that are appropriately location-tagged from social media. By analyzing spatial distributions of text tags from Flickr's geotagged photos, we identify thousands of tags that likely refer to ...
Chia-Kai Liang, Yu-Ting Hsieh, Tien-Jung Chuang, Yin Wang, Ming-Fang Weng, Yung-Yu Chuang   +5 more
openaire   +1 more source

Automatically Learning HTN Methods from Landmarks

The International FLAIRS Conference Proceedings
Hierarchical Task Network (HTN) planning usually requires a domain engineer to provide manual input about how to decompose a planning problem. Even HTN-MAKER, a well-known method-learning algorithm, requires a domain engineer to annotate the tasks with information about what to learn.
Ruoxi Li, Dana Nau, Mark Roberts, Morgan Fine-Morris   +3 more
openaire   +3 more sources

A comparison of modeling approaches for static and dynamic prediction of central-line bloodstream infections using electronic health records (part 1): regression models

Diagnostic and Prognostic Research
Background Hospitals register information in the electronic health records (EHRs) continuously until discharge or death. As such, there is no censoring for in-hospital outcomes.
Shan Gao, Elena Albu, Hein Putter, Pieter Stijnen, Frank E Rademakers, Veerle Cossey, Yves Debaveye, Christel Janssens, Ben Van Calster, Laure Wynants   +9 more
doaj   +1 more source