Other

Kaustav Banerjee

Abhishek Biswas

Samudraneel Saha

Samudra Neel Saha

A method for training a convolutional neural network comprises sliding a first, a second and a third window in a predefined path simultaneously on each training image of a training data set, a binary image containing a highlighted region of interest of the each training image, and a labeled image containing a plurality of tags representing one or more features of interest of the each training image. A target matrix is obtained for each sample of the labeled image that lies within the highlighted region of interest. The target matrix is a probabilistic distribution of the plurality of tags that is based on a proportion of existence of a feature of interest represented by a tag in the each sample. The CNN is trained to recognize each sample to contain the proportion of the at least one feature of interest based on the target matrix of the each sample.

Pattern recognition by convolutional neural networks

The present disclosure generally relates to analysis and detection of human emotions, and more particularly, to a method and system for detection of human emotion based on an individual's typing behavior. In one embodiment, the method comprises of receiving typing data of the individual for a specified amount of time, processing the received data to extract hand speed and key-press duration for the individual and analyzing the hand speed and key-press duration to detect probable emotional states the individual has experienced for the specified amount of time.

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Kolkata, India

Kaustav Banerjee