The machine learning has many capabilities one of them is classification. Classification employed in many contexts like telling hotel reviews good / bad, or inferring the image consists of dog, cat etc. As the data increases there is a need to organize it, for that purpose classification can be helpful. Modern classification problems involve the prediction of multiple labels simultaneously associated with a single instance known as "Multi Label Classification". In multi-label classification, each of the input data samples belongs to one or more than one classes or labels. The traditional binary and multi-class classification problems are the subset of the multi-label classification problem. In this paper we are implementing the multi label classification using CNN framework with keras libraries. Classification can be applied to different domain such as text, audio etc. In this paper we are applying classification for an image dataset.
This research is truly on an digital device which can be used on the time of emergency at the same time using a auto .It has embedded the concept of wireless communication i.E. Zigbee and GSM and many different sensors by using the help of which immediate help will also be delivered to the man or woman who has met with an accident .The total constitution is based on the microcontroller. Also the key function of has been implied through the support of which suitable consumer can manage the safety options of automobile if it is theft. Study content makes use of the science of Zigbee for the transmission of message to the other vehicle in the time of want of their support as well as for serving the potential of dependable and sound driving the features like drivers alcohol detection, car speed slowing and automatic car lock with collision detection is used. The GPS is also being used here for finding the distinct vehicle location in order that it may be located if lost.
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