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citations
Cited by 91 publications
(28 citation statements)
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“…CNNs have taken advantage over other approaches due to their effective ability to learn informative features from the data. These improvements lead to an enhancement of the accuracy performance, which is a decisive factor in use cases such as surveillance systems (Ko, ), cattle control (Kellenberger, Volpi, & Tuia, ), and search and rescue operations (Bejiga, ).…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…CNNs have taken advantage over other approaches due to their effective ability to learn informative features from the data. These improvements lead to an enhancement of the accuracy performance, which is a decisive factor in use cases such as surveillance systems (Ko, ), cattle control (Kellenberger, Volpi, & Tuia, ), and search and rescue operations (Bejiga, ).…”
Section: Related Workmentioning
confidence: 99%
“…These improvements lead to an enhancement of the accuracy performance, which is a decisive factor in use cases such as surveillance systems (Ko, 2018), cattle control (Kellenberger, Volpi, & Tuia, 2017), and search and rescue operations (Bejiga, 2016).…”
Section: Introductionmentioning
confidence: 99%
“…A unified framework based on deep convolutional neural network [9] was proposed for detection of abnormal behavior in video surveillance system. It solved the problem of separating object entities by human subject detection and discrimination module.…”
Section: Literature Surveymentioning
confidence: 99%
“…This is a type of learning network whereby the labels of normal and abnormal behaviors are given beforehand correspond to the situations. The network takes the input features and also the labels for training [3] - [6]. If the label of the test sample matches the training sample that contains normal behavior, it is classified as normal behavior, whereas if not, then is classified as abnormal behavior.…”
Section: Related Workmentioning
confidence: 99%
“…For supervised learning approach, Ko et al [3] proposed deep convolutional framework. The input image is first fed into the CNN and applied with Kalman filter.…”
Section: Related Workmentioning
confidence: 99%