The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform

Masaki Nakagawa - One of the best experts on this subject based on the ideXlab platform.

  • OST@ICDAR - Interactive User Interface for Recognizing Online Handwritten Mathematical Expressions and Correcting Misrecognition
    2019 International Conference on Document Analysis and Recognition Workshops (ICDARW), 2019
    Co-Authors: Vu Tran Minh Khuong, Minh Khanh Phan, Masaki Nakagawa
    Abstract:

    This paper presents an Interactive User interface for the recognition of online handwritten mathematical expressions (HMEs). Since the recognition results may have errors, our objective is to make a User interface by which the Users could verify and edit the recognition result of an HME easily without rewriting it. Multiple editing gestures are proposed to correct recognition errors in symbol recognition, symbol segmentation, and structure analysis. We implemented prototypes and conducted a User study to compare two variations for the User interface and a few variations for gestures. The results show that participants prefer the User interface showing the recognition result of each symbol apart from its bounding box to the one which embeds the recognition result into its bounding box. Moreover, the User study confirmed that our correcting gestures enable the Users to modify the recognition result as they expected.

  • Interactive User Interface for Recognizing Online Handwritten Mathematical Expressions and Correcting Misrecognition
    2019 International Conference on Document Analysis and Recognition Workshops (ICDARW), 2019
    Co-Authors: Vu Tran Minh Khuong, Minh Khanh Phan, Masaki Nakagawa
    Abstract:

    This paper presents an Interactive User interface for the recognition of online handwritten mathematical expressions (HMEs). Since the recognition results may have errors, our objective is to make a User interface by which the Users could verify and edit the recognition result of an HME easily without rewriting it. Multiple editing gestures are proposed to correct recognition errors in symbol recognition, symbol segmentation, and structure analysis. We implemented prototypes and conducted a User study to compare two variations for the User interface and a few variations for gestures. The results show that participants prefer the User interface showing the recognition result of each symbol apart from its bounding box to the one which embeds the recognition result into its bounding box. Moreover, the User study confirmed that our correcting gestures enable the Users to modify the recognition result as they expected.

Vu Tran Minh Khuong - One of the best experts on this subject based on the ideXlab platform.

  • OST@ICDAR - Interactive User Interface for Recognizing Online Handwritten Mathematical Expressions and Correcting Misrecognition
    2019 International Conference on Document Analysis and Recognition Workshops (ICDARW), 2019
    Co-Authors: Vu Tran Minh Khuong, Minh Khanh Phan, Masaki Nakagawa
    Abstract:

    This paper presents an Interactive User interface for the recognition of online handwritten mathematical expressions (HMEs). Since the recognition results may have errors, our objective is to make a User interface by which the Users could verify and edit the recognition result of an HME easily without rewriting it. Multiple editing gestures are proposed to correct recognition errors in symbol recognition, symbol segmentation, and structure analysis. We implemented prototypes and conducted a User study to compare two variations for the User interface and a few variations for gestures. The results show that participants prefer the User interface showing the recognition result of each symbol apart from its bounding box to the one which embeds the recognition result into its bounding box. Moreover, the User study confirmed that our correcting gestures enable the Users to modify the recognition result as they expected.

  • Interactive User Interface for Recognizing Online Handwritten Mathematical Expressions and Correcting Misrecognition
    2019 International Conference on Document Analysis and Recognition Workshops (ICDARW), 2019
    Co-Authors: Vu Tran Minh Khuong, Minh Khanh Phan, Masaki Nakagawa
    Abstract:

    This paper presents an Interactive User interface for the recognition of online handwritten mathematical expressions (HMEs). Since the recognition results may have errors, our objective is to make a User interface by which the Users could verify and edit the recognition result of an HME easily without rewriting it. Multiple editing gestures are proposed to correct recognition errors in symbol recognition, symbol segmentation, and structure analysis. We implemented prototypes and conducted a User study to compare two variations for the User interface and a few variations for gestures. The results show that participants prefer the User interface showing the recognition result of each symbol apart from its bounding box to the one which embeds the recognition result into its bounding box. Moreover, the User study confirmed that our correcting gestures enable the Users to modify the recognition result as they expected.

Matthew Kyan - One of the best experts on this subject based on the ideXlab platform.

  • Interactive User oriented visual attention based video summarization and exploration framework
    2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE), 2014
    Co-Authors: Yiming Qian, Matthew Kyan
    Abstract:

    An Interactive User oriented high definition visual attention based video summarization and exploration framework is proposed to extract feature frames from a video collection and allow Users to Interactively explore those feature frames. It is based on previous work [1] that applies high definition visual attention algorithm mapping and multivariate mutual information to select a feature frames to represent each shot, then uses a self-organizing map to remove the redundant frames. After the video summary process, the extracted feature frames are connected into a network structure. Each node contains the information of the feature frame and the relation to other nodes. The relation between nodes are defined by clustering algorithms (self-organizing map, k-means, support vector machine, etc), expert systems (look-up table, fuzzy logic statement, etc) or any algorithm that defines similarity (sift, surf, etc). When a User select one node, depending on the User setting, the related nodes will be displayed onto a 2D canvas. In this way User is be able to Interactively to browse through the whole video collection.

  • CCECE - Interactive User oriented visual attention based video summarization and exploration framework
    2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE), 2014
    Co-Authors: Yiming Qian, Matthew Kyan
    Abstract:

    An Interactive User oriented high definition visual attention based video summarization and exploration framework is proposed to extract feature frames from a video collection and allow Users to Interactively explore those feature frames. It is based on previous work [1] that applies high definition visual attention algorithm mapping and multivariate mutual information to select a feature frames to represent each shot, then uses a self-organizing map to remove the redundant frames. After the video summary process, the extracted feature frames are connected into a network structure. Each node contains the information of the feature frame and the relation to other nodes. The relation between nodes are defined by clustering algorithms (self-organizing map, k-means, support vector machine, etc), expert systems (look-up table, fuzzy logic statement, etc) or any algorithm that defines similarity (sift, surf, etc). When a User select one node, depending on the User setting, the related nodes will be displayed onto a 2D canvas. In this way User is be able to Interactively to browse through the whole video collection.

Minh Khanh Phan - One of the best experts on this subject based on the ideXlab platform.

  • OST@ICDAR - Interactive User Interface for Recognizing Online Handwritten Mathematical Expressions and Correcting Misrecognition
    2019 International Conference on Document Analysis and Recognition Workshops (ICDARW), 2019
    Co-Authors: Vu Tran Minh Khuong, Minh Khanh Phan, Masaki Nakagawa
    Abstract:

    This paper presents an Interactive User interface for the recognition of online handwritten mathematical expressions (HMEs). Since the recognition results may have errors, our objective is to make a User interface by which the Users could verify and edit the recognition result of an HME easily without rewriting it. Multiple editing gestures are proposed to correct recognition errors in symbol recognition, symbol segmentation, and structure analysis. We implemented prototypes and conducted a User study to compare two variations for the User interface and a few variations for gestures. The results show that participants prefer the User interface showing the recognition result of each symbol apart from its bounding box to the one which embeds the recognition result into its bounding box. Moreover, the User study confirmed that our correcting gestures enable the Users to modify the recognition result as they expected.

  • Interactive User Interface for Recognizing Online Handwritten Mathematical Expressions and Correcting Misrecognition
    2019 International Conference on Document Analysis and Recognition Workshops (ICDARW), 2019
    Co-Authors: Vu Tran Minh Khuong, Minh Khanh Phan, Masaki Nakagawa
    Abstract:

    This paper presents an Interactive User interface for the recognition of online handwritten mathematical expressions (HMEs). Since the recognition results may have errors, our objective is to make a User interface by which the Users could verify and edit the recognition result of an HME easily without rewriting it. Multiple editing gestures are proposed to correct recognition errors in symbol recognition, symbol segmentation, and structure analysis. We implemented prototypes and conducted a User study to compare two variations for the User interface and a few variations for gestures. The results show that participants prefer the User interface showing the recognition result of each symbol apart from its bounding box to the one which embeds the recognition result into its bounding box. Moreover, the User study confirmed that our correcting gestures enable the Users to modify the recognition result as they expected.

Zhimei Jiang - One of the best experts on this subject based on the ideXlab platform.

  • ICC - Performance of a wireless data network with mixed Interactive User workloads
    2002 IEEE International Conference on Communications. Conference Proceedings. ICC 2002 (Cat. No.02CH37333), 2002
    Co-Authors: N.k. Shankaranarayanan, A. Rastogi, Zhimei Jiang
    Abstract:

    Wireless data networks will have a mix of User workloads since there will be a variety of wireless data terminal devices. Using computer simulation, we study the performance of an EDGE-based packet wireless network with various combinations of Web and dataphone Users. We provide an understanding of the performance of a shared channel with mixed User workloads, and show that the number of Users that can be supported can be determined using simple rules based on average traffic statistics.

  • Performance of a wireless data network with mixed Interactive User workloads
    2002 IEEE International Conference on Communications. Conference Proceedings. ICC 2002 (Cat. No.02CH37333), 2002
    Co-Authors: N.k. Shankaranarayanan, A. Rastogi, Zhimei Jiang
    Abstract:

    Wireless data networks will have a mix of User workloads since there will be a variety of wireless data terminal devices. Using computer simulation, we study the performance of an EDGE-based packet wireless network with various combinations of Web and dataphone Users. We provide an understanding of the performance of a shared channel with mixed User workloads, and show that the number of Users that can be supported can be determined using simple rules based on average traffic statistics.