Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Author: search.filters.author.Yuvaraj, C.B.Has files: No

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    An approach to maintain attendance using image processing techniques
    (Institute of Electrical and Electronics Engineers Inc., 2017) Yuvaraj, C.B.; Madikeri, M.; Santhosh Kumar, V.; Vishnu Srinivasa Murthy, Y.V.; Koolagudi, S.G.
    Nowadays, the research is growing towards the invention of new approaches. One such most attracted application is face recognition of image processing. There are several innovative technologies have been developed to take attendance. Some prominent ones are biometric, thumb impressions, access card, and fingerprints. The method proposed in this paper is to record the attendance through image using face detection and face recognition. The proposed approach has been implemented in four steps such as face detection, labelling the detected faces, training a classifier based on labelled dataset, and face recognition. The database has been constructed with the positive images and negative images. The complete database has been divided into training and testing set and further, processed by a classifier to recognize the faces in a classroom. The final step is to take the attendance using face recognition technique in which the input image of a classroom is given, and faces of the given image will be detected along with their IDs. The frames of a video taken for a minute is taken into consideration to avoid the missed ones due to rotational issues. © 2017 IEEE.
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    Enhanced Last-Touch Interaction Attribution Model in Online Advertising
    (Institute of Electrical and Electronics Engineers Inc., 2018) Yuvaraj, C.B.; Chandavarkar, B.R.; Kumar, V.S.; Sandeep, B.S.
    The increased popularity of an internet opened a new way for e-business in terms of digital advertisement. In order to get back and improve the "return of investment", how to allocate the revenue distribution to different marketing channels comes out to be the key problem in digital advertising. However, last interaction model, first interaction model, last click, last ad words' click, linear attribution, time-decay attribution, position based attribution models are some of the attribution models developed to attribute and assign contribution to each marketing channel. These existing models consider the contributions of the other channels and some don't consider the synergistic effects in revenue calculation from different marketing channels. This paper proposes Enhanced Last Touch Interaction (ELTI) model to allocate the revenue distribution to different marketing channels using game theory and synergistic effects. Additionally, the paper also implements and adopts the probabilistic approaches to prevent the simple intuitions made by many other attribution models. Prediction accuracy of above 75% of the ELTI model out performance the state-of-the art models. © 2018 IEEE.