Multi-Modal Iris Recognition System based on Convolution Neural Network

Iris is most promising bio-metric trait for identification or authentication. Iris consists of patterns that are unique and highly random in nature .The discriminative property of iris pattern has attracted many researchers attention. The unimodal system, which uses only one bio-metric trait, suffers from limitation such as inter-class variation, intra-class variation and non-universality. The multi-modal bio-metric system has ability to overcome these drawbacks by fusing multiple biometric traits. In this paper, a multi-modal iris recognition system is proposed. The features are extracted using convolutional neural network and softmax classifier is used for multi-class classification. Finally, rank level fusion method is used to fuse right and left iris in order to improve the confidence level of identification. This method is tested on two data sets namely IITD and CASIA-Iris-V3.

The Instrumentally Derived Incentive-Motivational Function

Though differential reinforcement, a discriminative stimulus (SD) acquires two properties. The operant contingency is responsible for the SDs response-discriminative property. However, as stimulus control develops an SD also acquires incentive-motivational properties through its association with reinforcement changes. A systematic series of experiments are described that breaks the usual co-variation of response and reinforcement rates in most discriminative operant situations. In three groups, SDs (a tone and a light) occasioned steady moderate lever pressing in rats that ceased when neither SD was present. Probably of reinforcement in these SDs, relative to when both were off, was systematically manipulated to make them incentive-motivationally excitatory, neutral or inhibitory. In each SD, for the “excitatory” group reinforcement (food) probability increased from 0 to 100%, for the “neutral” group it was unchanged and for the “inhibitory” group it decreased from 100 to 0%. Although behaviorally indistinguishable in training, a stimulus-compounding assay revealed that tone-plus-light tripled response rate in the incentive-excitatory group, doubled rate in the incentive-neutral group and didn’t increase rate in the incentive-inhibitory group – producing the instrumentally derived incentive-motivational function for the first time. This is discussed context of two-process learning theory, a functional analysis of transfer-of-control research plus how the response-discriminative and incentive-motivational properties acquired by an SD contribute to the stimulus control of behavior.