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Underwater object identification based on acoustic sequence is a complex task, mainly, because of the non-stationary nature of the underwater environment. Moreover, the ambient conditions contribute heavily to varying temporal and spectral characteristics of the source. Further, the characteristic features of a source lie within its spectrum whereas pure spectral contents are more robust to variations...
Iris recognition has proved to be one of the most reliable and stable biometric for human identification. This paper outlines an iris recognition approach based on deep learning. In addition, contour based feature vector has been used to discriminate samples belonging to different classes i.e. difference of sclera-iris and iris-pupil contours, and is named as “Unique Signature”. Moreover, contours...
In a data communication network, several flows contend to utilize limited and shared network resources, however, this gives rise to congestion along with other network issues. So, this leads to the development of congestion control based methods/ protocols to support the deployment of real-time multimedia applications while ensuring reliability and fairness. This paper presents a simulation based...
This paper presents a novel approach towards iris recognition based on dual boundary (Pupil-Iris & Sclera-Iris) detection and then using a modified Multilayer Feed Forward neural network (MFNN) to perform an efficient automatic classification. The novelty of the work resides in the fact that the proposed method features the localization of the dual iris boundaries to be used as feature vector...
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