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I tried your ris_ei.bif for EI search. It worked fine with Journal papers. Unfortunately, it had some problems with Conference papers. It seemed a "BT" field was missing in the filter. Please try the two examples below. By the way, regarding to the filter for IEEE. What kind of examples do you need? The one in my last post was not enough? I'm glad to make more for you.

Thanks a lot!

TY  - CONF
N1  - Compilation and indexing terms, Copyright 2006 Elsevier Inc. All rights reserved
TI  - Extending the prediction error coder of H.264/AVC by a vector quantizer
BT  - Visual Communications and Image Processing 2005, Jul 12-15 2005
T3  - Proceedings of SPIE - The International Society for Optical Engineering
A1  - Narroschke, Matthias
AD  - Institut fur Theoretische Nachrichtentechnik und Informationsverarbeitung, Universitat Hannover, 30167 Hannover, Germany
VL  -  5960
IS  -  4
PY  - 2005
U1  - 06089710738
SP  - 2267
EP  - 2278
SN  - 0277-786X
CY  - Beijing, China
PB  - International Society for Optical Engineering, Bellingham WA, WA 98227-0010, United States
N2  - The standardized video coding algorithms are based on hybrid coding using blockwise motion compensated prediction and transform coding of the resulting prediction error. For the purpose of transform coding, the recent standard H.264/AVC applies an integer transform. For each block, the Lagrangian costs are analyzed, which are measured by the sum of the squared reconstruction errors and the bit rate weighted by a Lagrange multiplier. It is observed that the costs of blocks with marginally or diagonally correlated samples are frequently higher than the costs theoretically required due to the fact that the transform coder of H.264/AVC is unadjusted for these blocks. In this paper, it is investigated if the coding efficiency can be improved by extending the prediction error coder by a vector quantizer which is optimized for the coding of these blocks. For each block of the prediction error either standardized transform coding or vector quantization is applied whereas the algorithm with lower costs is chosen. For broadcast quality at 34 dB PSNR, the bit rate is reduced by 7-10% compared to H.264/AVC using CAVLC with slightly reduced computational expense in the decoder. Compared to H.264/AVC using CABAC, almost the same coding efficiency is achieved with significantly lower computational expense in the decoder.
KW  - Image coding
KW  - Vector quantization
KW  - Error analysis
KW  - Lagrange multipliers
KW  - Image reconstruction
KW  - Bit error rate
U2  - H.264/AVC
U2  - MPEG
U2  - ITU
L2  - http://dx.doi.org/10.1117/12.633517
ER  -

TY  - CONF
N1  - Compilation and indexing terms, Copyright 2006 Elsevier Inc. All rights reserved
TI  - Bayes-risk minimized intra/Inter coding mode prediction for H.264
BT  - Proceedings of SPIE-IS and T Electronic Imaging - Image and Video Communications and Processing 2005, Jan 18-20 2005
T3  - Proceedings of SPIE - The International Society for Optical Engineering
A1  - Kim, Changsung
A1  - Kuo, C.-C. Jay
AD  - Integrated Media Systems Center, Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90089-2564, United States
VL  -  5685
IS  -  PART 2
PY  - 2005
U1  - 05299222260
SP  - 1053
EP  - 1064
SN  - 0277-786X
CY  - San Jose, CA, United States
PB  - International Society for Optical Engineering, Bellingham, WA 98227-0010, United States
N2  - A feature-based coding mode prediction method is proposed to reduce the encoder complexity of the H.264 video coding standard in this work. The current H.264 reference codes employ exhaustive search to find the best mode that optimizes the rate-distortion performance among all possible intra/inter predictive modes. To develop a fast binary intra/inter-mode prediction scheme, we consider the expected risk of choosing the wrong mode in a multi-dimensional feature space. The proposed algorithm consists of three steps. First, three features are extracted from the current macroblock. Second, the expected risk is calculated for the corresponding partition in the trained feature vector space, which is used to decide where the feature vector lies in one of the three regions depending on the expected risk, i.e. risk-free, risk-tolerable, and risk-intolerable regions. Finally, depending on the region to which the feature vector belongs, we can apply mechanisms of different complexities for final mode decision. For the likelihood estimation of the risk, parametric and non-parametric density estimation schemes are compared in terms of the rate-distortion-complexity tradeoff. It is demonstrated by experimental results that the proposed algorithm can save approximately 20-32% of the total encoding time of H.264 (JM7.3a) with little degradation in the rate-distortion performance. © 2005 SPIE and IS and T.
KW  - Image coding
KW  - Algorithms
KW  - Computational complexity
KW  - Vectors
KW  - Lagrange multipliers
KW  - Binary codes
KW  - Parameter estimation
U2  - H.264/AVC
U2  - Coding mode prediction
U2  - Bayes-risk minimization
U2  - Density estimation
U2  - Mode decision
U2  - Encoder complexity
L2  - http://dx.doi.org/10.1117/12.589887
ER  -