Mohak Sukhwani

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We propose an end-to-end recurrent encoder-decoder based sequence learning approach for printed text Optical Character Recognition (OCR). In contrast to present day existing state-of-art OCR solution [Graves et al. (2006)] which uses CTC output layer, our approach makes minimalistic assumptions on the structure and length of the sequence. We use a two step(More)
Automatically describing videos has ever been fascinating. In this work, we attempt to describe videos from a specific domain – broadcast videos of lawn tennis matches. Given a video shot from a tennis match, we intend to generate a textual commentary similar to what a human expert would write on a sports website. Unlike many recent works that focus on(More)
In this paper, we present a parameterized approach to produce personalized variable length summaries of soccer matches. Our approach is based on temporally segmenting the soccer video into “plays”, associating a user-specifiable “utility” for each type of play and using “bin-packing” to select a subset of the plays that add up to the desired length while(More)
Recently, quadcopters with their advance sensors and imaging capabilities have become an imperative part of the precision agriculture. In this work, we have described a framework which performs plantation monitoring and yield estimation using the supervised learning approach, while autonomously navigating through an inter-row path of the plantation. The(More)
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