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Recently, capabilities of many computer vision tasks have significantly improved due to advances in Convolutional Neural Networks. In our research, we demonstrate that it can be also used for face detection from low resolution thermal images, acquired with a portable camera. The physical size of the camera used in our research allows for embedding it in a wearable device or indoor remote monitoring...
Deep feature learning methods have been aggressively applied in the field of music tagging retrieval Genre categorization, mood classification, and chord detection are the most common tags from local spectral to temporal structure. Convolutional Neural networks (CNNs) using kernels extract the local features that are in different levels of hierarchy while Recurrent Neural Networks (RNNs) discover...
Speaker identification systems are becoming more important in today's world. This is especially true as devices rely on the user to speak commands. In this article, an analysis of how a text-independent voice identification system can be built is presented. Extracting the Mel-Frequency Cepstral Coefficients is evaluated and a support vector machine is trained and tested on two different data sets,...
Pedestrian recognition is a key problem for a number of application domains namely autonomous driving, search and rescue, surveillance and robotics. Real-time pedestrian recognition entails determining if a pedestrian is in an image frame. State-of-art pedestrian detection convolution neural networks(CNN) such as Fast R-CNN depend on computationally expensive region detection algorithms to hypothesize...
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