STM Journals Peer-reviewed research from Consortium e-Learning Network

3 publications

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    Enhancing Resolution of Artifact Image using AR-CNN and SRGAN

    By Swagato Das, Uttam Paul, S.M. Mohidul Islam

    Abstract: Abstract The super-resolution strategy recreates a higher-resolution image or arrangement from the observed low resolutions (LR) images. As super-resolution has been created for over three decades, both multi-casing and single-outline super-resolution has critical applications in our everyday life. Existing super-resolution strategies have a few constraints. The artifact is additionally an issue in compression of an image. With artifacts, the high-resolution image is most noticeably terrible to see. In this paper, …

    Published in Journal of Computer Technology & Applications · Vol. 11, Issue 3, 2020 · pp. 12–19 Read article

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    Partial View-Based Object Recognition using Leave-one-out Approach with Classification and Regression Trees

    By S.M. Mohidul Islam, Farhana Tazmim Pinki

    Abstract: Object recognition from image is an intriguing task in computer vision. It is simple for human being but complex for machine because of complex background, lightening, different viewing angle, size etc. So, a typically automatic and robust system is required to recognize object. In this paper, a content-based object recognition system using only one view of the object: top view, front view, back view, side view, and also using combination …

    Published in Journal of Computer Technology & Applications · Vol. 9, Issue 3, 2018 · pp. 9–16 Read article

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    Temporal Information Extraction from Textual Data using Long Short Term Memory Recurrent Neural Network

    By Tanvir Hossain, Md. Mostafijur Rahman, S.M. Mohidul Islam

    Abstract: Temporal information extraction from raw text is always challenging. It is time consuming and sometimes difficult to extract temporal expression manually. For this reason, an automatic system is a demand to find the temporal expressions from the textual data automatically. In this paper, we have developed a temporal information extraction system using Long Short Term Memory (LSTM) recurrent neural network (RNN) along with word embedding where temporal expressions are extracted …

    Published in Journal of Computer Technology & Applications · Vol. 9, Issue 2, 2018 · pp. 1–6 Read article

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