Published Paper Details:

It's important to save archaeological monuments as they play a pivotal part in helping us understand mortal history and their accomplishments for times with no or little spoken sources. The first step for this purpose is an effective system for collecting and establishing information about objects of interest for archaeologists. One of the best way to automate this process is using deep neural networks. Archaeology is the scientific study of mortal history. Computers have been used in the field of archaeology for multitudinous times and it has now come an essential wide tool for archaeologists. As the use or operation of computers becomes increasingly necessary to the work of the archaeologist, which they bear a clear understanding of the impact of information technology upon their discipline. In this work, we propose a hierarchical Convolutional Neural Network (CNN) model to classify archaeological objects, artifacts. This paper explains the influence and the development of computers on all aspects of archaeological disquisition and interpretation, from check, excavation and museums to galleries, education and communicating the history. To compare and validate our system, we run trials on the same data set using deep knowledge model. The instigation of the computers can begin with the appraisal at all stages of archaeological disquisition and data analysis. The main themes to materialize are the eventuality of computers as active agents for study rather than as just unresisting tools, and the symbiotic relationship between the development of digital technologies and archaeological proposition.