Abstract
Concept identification and automated image annotation helps to overcome the non-trivial issue of image retrieval. It is accomplished by decomposing the image at object level and extracting concepts from objects. Several applications like biometrics, geographical information systems, and automatic target recognition possess highly diffused feature vectors. Hence, a conventional Artificial Neural Network (ANN) fails to deliver truthful results. In this work, we have developed a modified back propagation algorithm and have proposed a novel topology in Modular Artificial Neural Network (MANN) to rectify the problem faced in concept identification. In this topology we have trained each module of ANN for one object in one verse all fashion and highly ranked output is taken as classified output. Our argument is supported by combined application of afore-mentioned algorithm and novel topology using MATLAB simulations on two different datasets.