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sceneclassification icon sceneclassification

Scene classification is a problem under the domain of object recognition. Scene classification is a very interesting problem of automatically labeling an image among a set of semantic categories. To achieve this, we had implemented a Bag Of Words model and used Cornell's SVMLight to train and classify the data.

sceneclassification-2 icon sceneclassification-2

This project is to use deep learning to auto classify the scene images with limited amount of training images.

sceneclassification-7 icon sceneclassification-7

This is a scene recognition system using Bag of Words approach. Filters like edge detectors are used to extract features and Bag of Words is created using k-means clustering algorithm. Finally spatial pyramid matching using image histograms is done to create word map and perform classification.

schedule icon schedule

Scheduler for MatConvNet experiments, including grid and random searches, with multi-GPU support.

scheduler-sandbox icon scheduler-sandbox

Sandbox area for simple, sample code related to the isetbio "Scheduler" architecture.

schellingsegregationmodel icon schellingsegregationmodel

As part of Modelling and Simulation project, we had implemented this famous Schelling’s model which looks at the segregation of the two groups in particular area. We implemented this model using the rules of cellular automata.

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