Image Processing
The dataset consists of 60285 character image files which has been randomly divided into 54239 (90%) images as training set 6046 (10%) images as test set. The collection of data samples was carried out in two phases. The first phase consists of distributing a tabular form and asking people to write the characters five times each. Filled-in forms were collected from around 200 different individuals in the age group 12-23 years. The second phase was the collection of handwritten sheets such as answer sheets and classroom notes from students in the same age group.
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As one of the research directions at OLIVES Lab @ Georgia Tech, we focus on the robustness of data-driven algorithms under diverse challenging conditions where trained models can possibly be depolyed. To achieve this goal, we introduced a large-sacle (1.M images) object recognition dataset (CURE-OR) which is among the most comprehensive datasets with controlled synthetic challenging conditions. In CURE
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As one of the research directions at OLIVES Lab @ Georgia Tech, we focus on the robustness of data-driven algorithms under diverse challenging conditions where trained models can possibly be depolyed. To achieve this goal, we introduced a large-sacle (~1.72M frames) traffic sign detection video dataset (CURE-TSD) which is among the most comprehensive datasets with controlled synthetic challenging conditions. The video sequences in the
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This data set contains 50 low resolution (640 x 360) short videos containing a variety real life activities.
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This Dataset consist of 3Dmodels in Spherical harmonic coefficients andcorresponding shortcut of front view, the SH degree is 80.
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The modified CASIA dataset is created for research topics like: perceptual image hash, image tampering detection, user-device physical unclonable function and so on.
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As one of the research directions at OLIVES Lab @ Georgia Tech, we focus on the robustness of data-driven algorithms under diverse challenging conditions where trained models can possibly be depolyed.
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3934 Views
This dataset includes all letters from Turkish Alphabet in two parts. In the first part, the dataset was categorized by letters, and the second part dataset was categorized by fonts. Both parts of dataset includes the features mentioned below.
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72, 20 AND 8 POINT LETTERS
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UPPER AND LOWER CASES
The all characters in Turkish Alphabet are included (a, b, c, ç, d, e, f, g, ğ, h, ı, i, j, k, l, m, n, o, ö, p, r, s, ş, t, u, ü, v, y, z).
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The Dataset
The Onera Satellite Change Detection dataset addresses the issue of detecting changes between satellite images from different dates.
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基于波动算法的快速视网膜分割
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