Results 291 to 300 of about 6,515,077 (343)
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Clinical EEG and Neuroscience, 2009
Since the 1970s advances in science and technology during each succeeding decade have renewed the expectation of efficient, reliable automatic epileptiform spike detection (AESD). But even when reinforced with better, faster tools, clinically reliable unsupervised spike detection remains beyond our reach.
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Since the 1970s advances in science and technology during each succeeding decade have renewed the expectation of efficient, reliable automatic epileptiform spike detection (AESD). But even when reinforced with better, faster tools, clinically reliable unsupervised spike detection remains beyond our reach.
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Automatic Detection and Classification of Sewer Defects via Hierarchical Deep Learning
IEEE Transactions on Automation Science and Engineering, 2019Video and image sources are frequently applied in the area of defect inspection in industrial community. For the recognition and classification of sewer defects, a significant number of videos and images of sewers are collected.
Qian Xie +4 more
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IEEE Transactions on Terahertz Science and Technology, 2019
The automatic extraction of the targets in which we are interested from a given image is the fundamental of the automatic detection and identification for security screening systems based on imaging technologies.
Rui Li +4 more
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The automatic extraction of the targets in which we are interested from a given image is the fundamental of the automatic detection and identification for security screening systems based on imaging technologies.
Rui Li +4 more
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Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018
Endoscopic image diagnosis assisted by machine learning is useful for reducing misdetection and interobserver variability. Although many results have been reported, few effective methods are available to automatically detect early gastric cancer.
Yoshimasa Sakai +6 more
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Endoscopic image diagnosis assisted by machine learning is useful for reducing misdetection and interobserver variability. Although many results have been reported, few effective methods are available to automatically detect early gastric cancer.
Yoshimasa Sakai +6 more
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Automatic Detection of Burst Suppression
2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007Burst suppression pattern (BSP) as a common diffuse abnormal electroencephalographic (EEG) pattern requires close monitoring in the intensive care unit (ICU) environments. Automatic detection of individual BS events has a clinical and practical importance for brain function monitoring in the neurological ICUs (NICUs) using Continuous EEG (CEEG).
Yunhua, Wang, Rajeev, Agarwal
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Automatic Subpixel Detection: Anomaly Detection
2003One type of automatic target detection, unsupervised subpixel detection has been considered in Chapter 5. This chapter considers another type of automatic target detection, anomaly detection. Unlike the unsupervised subpixel detection, which requires generating a posteriori target information, anomaly detection does not need any target information at ...
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Automatic detection of orientation variance
Neuroscience Letters, 2017Rapid extraction of the overall statistics of the visual scene is crucial for the human ability to rapidly perceive the general 'gist'. The aim of this work was to investigate if there exists neural evidence for such a process i.e. automatic, unattended detection of overall statistical differences between scenes.
Szonya, Durant +2 more
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2022
This thesis was scanned from the print manuscript for digital preservation and is copyright the author. Researchers can access this thesis by asking their local university, institution or public library to make a request on their behalf. Monash staff and postgraduate students can use the link in the References field.
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This thesis was scanned from the print manuscript for digital preservation and is copyright the author. Researchers can access this thesis by asking their local university, institution or public library to make a request on their behalf. Monash staff and postgraduate students can use the link in the References field.
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An Automatic Detection System of Lung Nodule Based on Multigroup Patch-Based Deep Learning Network
IEEE journal of biomedical and health informatics, 2018High-efficiency lung nodule detection dramatically contributes to the risk assessment of lung cancer. It is a significant and challenging task to quickly locate the exact positions of lung nodules.
Hongyang Jiang +4 more
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2022
The aim of this exploratory project is to decrease the test time for correct detection of auditory responses. A correct detection occurs when a response is correctly identified as a response with a maximum of 5% of non-responses categorised as responses.
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The aim of this exploratory project is to decrease the test time for correct detection of auditory responses. A correct detection occurs when a response is correctly identified as a response with a maximum of 5% of non-responses categorised as responses.
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