Detection of Abandoned and Stolen Objects Based on Dual Background Model and Mask R-CNN

Park, Hyeseung; Park, Seung-Chul; Joo, Young-Bok

doi:10.1109/access.2020.2990618

Cited by 33 publications

(14 citation statements)

References 22 publications

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“…In [288], the target in the video is detected. The method used is based on traditional background subtraction and artificial intelligence detection.…”

Section: Potential Detection Methods On Wsi Technologymentioning

confidence: 99%

A Comprehensive Review of Computer-aided Whole-slide Image Analysis: from Datasets to Feature Extraction, Segmentation, Classification, and Detection Approaches

Li¹,

Li²,

Rahaman³

et al. 2021

Preprint

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With the development of computer-aided diagnosis (CAD) and image scanning technology, Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis. Therefore, WSI analysis has become the key to modern digital pathology. Since 2004, WSI has been used more and more in CAD. Since machine vision methods are usually based on semi-automatic or fully automatic computers, they are highly efficient and labor-saving. The combination of WSI and CAD technologies for segmentation, classification, and detection helps histopathologists obtain more stable and quantitative analysis results, save labor costs and improve diagnosis objectivity. This paper reviews the methods of WSI analysis based on machine learning. Firstly, the development status of WSI and CAD methods are introduced. Secondly, we discuss publicly available WSI datasets and evaluation metrics for segmentation, classification, and detection tasks. Then, the latest development of machine learning in WSI segmentation, classification, and detection are reviewed continuously. Finally, the existing methods are studied, the applicability of the analysis methods are analyzed, and the application prospects of the analysis methods in this field are forecasted.

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“…In [288], the target in the video is detected. The method used is based on traditional background subtraction and artificial intelligence detection.…”

Section: Potential Detection Methods On Wsi Technologymentioning

confidence: 99%

A Comprehensive Review of Computer-aided Whole-slide Image Analysis: from Datasets to Feature Extraction, Segmentation, Classification, and Detection Approaches

Li¹,

Li²,

Rahaman³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…In [96], the target in the video is detected. The method used is based on traditional background subtraction and artificial intelligence detection.…”

Section: Other Potential Methods Applied To Wsi Technologymentioning

confidence: 99%

A State-of-the-art Survey of Artificial Neural Networks for Whole-slide Image Analysis:from Popular Convolutional Neural Networks to Potential Visual Transformers

Li¹,

Li²,

Li³

et al. 2021

Preprint

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In recent years, with the advancement of computer-aided diagnosis (CAD) technology and whole slide image (WSI), histopathological WSI has gradually played a crucial aspect in the diagnosis and analysis of diseases. To increase the objectivity and accuracy of pathologists' work, artificial neural network (ANN) methods have been generally needed in segmentation, classification, and detection of histopathological WSI. In this paper, WSI analysis methods based on ANN are reviewed. Firstly, the development status of WSI and ANN methods is introduced. Secondly, we summarize the common ANN methods. Next, we discuss publicly available WSI datasets and evaluation metrics. These ANN architectures for WSI processing are divided into classical neural networks and deep neural networks (DNNs) and then analyzed. Finally, the application prospect of the analytical method in this field is discussed. The important potential method is Visual Transformers.

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“…Breakthrough in this field was by introducing the convolutional neural networks [11] which gave marvellous results. Numerous applications have developed such as object detection [12], image segmentation [13], biomedical applications [14] and many more. Recent trends include generating high quality images [15] and image translations [16].…”

Section: Related Workmentioning

confidence: 99%

Do Images really do the Talking? Analysing the significance of Images in Tamil Troll meme classification

Hegde,

Hande,

Priyadharshini

et al. 2021

Preprint

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A meme is an part of media created to share an opinion or emotion across the internet. Due to its popularity, memes have become the new forms of communication on social media. However, due to its nature, they are being used in harmful ways such as trolling and cyberbullying progressively. Various data modelling methods create different possibilities in feature extraction and turning them into beneficial information. The variety of modalities included in data plays a significant part in predicting the results. We try to explore the significance of visual features of images in classifying memes. Memes are a blend of both image and text, where the text is embedded into the image. We try to incorporate the memes as troll and non-trolling memes based

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Detection of Abandoned and Stolen Objects Based on Dual Background Model and Mask R-CNN

Cited by 33 publications

References 22 publications

A Comprehensive Review of Computer-aided Whole-slide Image Analysis: from Datasets to Feature Extraction, Segmentation, Classification, and Detection Approaches

A Comprehensive Review of Computer-aided Whole-slide Image Analysis: from Datasets to Feature Extraction, Segmentation, Classification, and Detection Approaches

A State-of-the-art Survey of Artificial Neural Networks for Whole-slide Image Analysis:from Popular Convolutional Neural Networks to Potential Visual Transformers

Do Images really do the Talking? Analysing the significance of Images in Tamil Troll meme classification

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