Blar i forfatter "Kar, Samarjit"

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    • Can We Automate Diagrammatic Reasoning? 

      Sekh, Arif Ahmed; Dogra, Debi Prasad; Kar, Samarjit; Roy, Partha Pratim; Prosad, Dilip K. (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-05-06)
      Diagrammatic reasoning (DR) problems are well known. However, solving DR problems represented in 4 × 1 Raven’s Progressive Matrix (RPM) form using computer vision and pattern recognition has not yet been tried. Emergence of deep learning techniques aided by advanced computing can be exploited to solve such DR problems. In this paper, we propose a new learning framework by combining LSTM and Convolutional ...

    • ELM-HTM guided bio-inspired unsupervised learning for anomalous trajectory classification 

      Sekh, Arif Ahmed; Dogra, Debi Prosad; Kar, Samarjit; Roy, Partha Pratim; Prasad, Dilip K. (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-05-23)
      Artificial intelligent systems often model the solutions of typical machine learning problems, inspired by biological processes, because of the biological system is faster and much adaptive than deep learning. The utility of bio-inspired learning methods lie in its ability to discover unknown patterns, and its less dependence on mathematical modeling or exhaustive training. In this paper, we propose ...

    • Neural network based country wise risk prediction of COVID-19 

      Pal, Ratnabali; Sekh, Arif Ahmed; Kar, Samarjit; Prasad, Dilip K. (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-09-16)
      The recent worldwide outbreak of the novel coronavirus (COVID-19) has opened up new challenges to the research community. Artificial intelligence (AI) driven methods can be useful to predict the parameters, risks, and effects of such an epidemic. Such predictions can be helpful to control and prevent the spread of such diseases. The main challenges of applying AI is the small volume of data and the ...

    • Neural Network Based Country Wise Risk Prediction of COVID-19 

      Pal, Ratnabali; Sekh, Arif Ahmed; Kar, Samarjit; Prasad, Dilip K. (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-09-16)
      The recent worldwide outbreak of the novel coronavirus (COVID-19) has opened up new challenges to the research community. Artificial intelligence (AI) driven methods can be useful to predict the parameters, risks, and effects of such an epidemic. Such predictions can be helpful to control and prevent the spread of such diseases. The main challenges of applying AI is the small volume of data and the ...

    • Topic-based Video Analysis: A Survey 

      Pal, Ratnabali; Sekh, Arif Ahmed; Dogra, Debi Prosad; Kar, Samarjit; Roy, Partha Pratim; Prasad, Dilip K. (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-07-13)
      Manual processing of a large volume of video data captured through closed-circuit television is challenging due to various reasons. First, manual analysis is highly time-consuming. Moreover, as surveillance videos are recorded in dynamic conditions such as in the presence of camera motion, varying illumination, or occlusion, conventional supervised learning may not work always. Thus, computer ...

    • Video trajectory analysis using unsupervised clustering and multi-criteria ranking 

      Sekh, Arif Ahmed; Dogra, Debi Prasad; Kar, Samarjit; Roy, Partha Pratim (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-05-13)
      Surveillance camera usage has increased significantly for visual surveillance. Manual analysis of large video data recorded by cameras may not be feasible on a larger scale. In various applications, deep learning-guided supervised systems are used to track and identify unusual patterns. However, such systems depend on learning which may not be possible. Unsupervised methods relay on suitable features ...