• Journal of Digital Contents Society
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• v.16 no.5
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• pp.671-680
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• 2015

The Joint Bayesian[1] method was published in 2012. Since then, it has been used for binary classification in almost all state-of-the-art face recognition methods. However, no improved methods have been published so far except 2D-JB[2]. In this paper we propose an improved version of the JB method that considers the features of both the given face image and its mirror image. In pattern classification, it is very likely to make a mistake when the value of the decision function is close to the decision boundary or the threshold. By making the value of the decision function far from the decision boundary, the proposed method reduces the errors. The experimental results show that the proposed method outperforms the JB and 2D-JB methods by more than 1% in the challenging LFW DB. Many state-of-the-art methods required tons of training data to improve 1% in the LFW DB, but the proposed method can make it in an easy way.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.381-391
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• 2016

The Joint Bayesian (JB) method has been used in most state-of-the-art methods for face verification. However, since the publication of the original JB method in 2012, no improved verification method has been proposed. A lot of studies on face verification have been focused on extracting good features to improve the performance in the challenging Labeled Faces in the Wild (LFW) database. In this paper, we propose an improved version of the JB method, called the two-dimensional Joint Bayesian (2D-JB) method. It is very simple but effective in both the training and test phases. We separated two symmetric terms from the three terms of the JB log likelihood ratio function. Using the two terms as a two-dimensional vector, we learned a decision line to classify same and not-same cases. Our experimental results show that the proposed 2D-JB method significantly outperforms the original JB method by more than 1% in the LFW database.

• Microbiology and Biotechnology Letters
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• v.31 no.4
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• pp.368-376
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• 2003

Cyclodextrin glucanotransferase (CGTase) from Paenibacillus sp. JB-13 was immobilized on various carriers by several immobilization methods such as ionic binding, covalent linkage and ultrafiltration to improve the process performance. The ultrafiltration and covalent linkage with CNBr-activated sepharose 4B were found as the best method for immobilization of CGTase. The ability of CGTase immobilization onto CNBr-activated sepharose 4B was as high as 18,000 units/g resin when the conditions was as follows: contact time 9 hrs at $37^{\circ}C$, pH 6.0, 100 nm and enzyme loading 24,000 units/g resin. The optimum conditions for production of 2-O-$\alpha$-D-Glucopyranosyl L-Ascorbic acid by immobilized CGTase turned out to be: pH 5.0, temperature $37^{\circ}C$, 20% substrate solution containing 8% (w/v) of soluble starch and 12% (w/v) of L-ascorbic acid sodium salt, 100 rpm, far 25 hrs and with 800 units of immobilized CGTase/ml substrate solution. Moreover the CGTase activity could be stably maintained for 8 times of repetitive reactions after removing products by ultrafiltration through YM 10 membrane.