![](\"https://m.media-amazon.com/images/M/MV5BZjdkOTU3MDktN2IxOS00OGEyLWFmMjktY2FiMmZkNWIyODZiXkEyXkFqcGdeQXVyMTMxODk2OTU@._V1_.jpg\")
\n\nFor movie lovers, the movie poster makes up the first impression about the movie contents and its genre. \n
Humans can grasp the cues like color, expressions on the faces of actors etc to quickly determine the genre (horror, comedy, animation etc) of a movie. Though it might seem simple, it involves millions of concurrent processes occurring in a less than a jiffy! If humans are able to inherently predict genre of a movie by a glance at its poster, can't we expect the same from a machine ?\n\n
It has been studied that the human brain tends to make intuitions based on the color characteristics, local texture based features and structural cues of posters. Hence, the posters possess some characteristics which could be utilized for genre classification
\n\nIn this competition, your goal is to predict the genres of movies from their posters.
\n\nThe evaluation metric for this competition is Mean F1-Score. The F1 score, commonly used in information retrieval, measures accuracy using the statistics precision p and recall r. Precision is the ratio of true positives (tp) to all predicted positives (tp + fp). Recall is the ratio of true positives to all actual positives (tp + fn). The F1 score is given by:
\n\\[ F1 = 2\\frac{p \\cdot r}{p+r}\\ \\ \\mathrm{where}\\ \\ p = \\frac{tp}{tp+fp},\\ \\ r = \\frac{tp}{tp+fn} \\]
\nThe F1 metric weights recall and precision equally, and a good retrieval algorithm will maximize both precision and recall simultaneously. Thus, moderately good performance on both will be favored over extremely good performance on one and poor performance on the other.
", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Timeline", "content": "February 3, 2020 - Team Merger deadline. This is the last day participants may join or merge teams.\n\nFebruary 5, 2020 - Final submission deadline.\n\nAll deadlines are at 11:59 PM IST on the corresponding day unless otherwise noted. The competition organizers reserve the right to update the contest timeline if they deem it necessary.", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Prizes", "content": "The following prizes will be awarded on the basis of private leader board rank after manually evaluating their submitted final kernels. If any discrepancy is found, then that participant will be not eligible for prize.\n\n1st Prize: ₹ 5000\n2nd Prize: ₹ 3000\n3rd Prize: ₹ 2000\n\nThe top two team with parcipants of 1st year of IIT (ISM) Dhanbad will get a chance for being recruited in AI Division of the Cyber Labs ", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Kernels Requirements", "content": "We are a team of individuals from multiple disciplines, driven by the desire of implementing solutions-unbounded by the limits of knowledge or technical know-how. The problem statement address issues ranging from solving social problems and cultural opportunities to building some cool gadgets. It was founded post inspiration on the footsteps of MIT Media Labs by an enthusiastic and ticking learner who discovered a scope beyond rote learning and plain-vanilla implementations of the common problems and sci-fi solutions.\nCyber Labs provides a platform to discuss debate and explore the viable and easy solutions, be it tech or non-tech to problems via a project-based approach.
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