Semantic transform: Weakly supervised semantic inference for relating visual attributes

Relative (comparative) attributes are promising for thematic ranking of visual entities, which also aids in recognition tasks. However, attribute rank learning often requires a substantial amount of relational supervision, which is highly tedious, and apparently impractical for real-world applications. In this paper, we introduce the Semantic Transform, which under minimal supervision, adaptively finds a semantic feature space along with a class ordering that is related in the best possible way. Such a semantic space is found for every attribute category. To relate the classes under weak supervision, the class ordering needs to be refined according to a cost function in an iterative procedure. This problem is ideally NP-hard, and we thus propose a constrained search tree formulation for the same. Driven by the adaptive semantic feature space representation, our model achieves the best results to date for all of the tasks of relative, absolute and zero-shot classification on two popular datasets. © 2013 IEEE.

Measurement of gain spectrum for Fabry-Perot semiconductor lasers by the Fourier transform method with a deconvolution process

To improve the accuracy of measured gain spectra, which is usually limited by the resolution of the optical spectrum analyzer (OSA), a deconvolution process based on the measured spectrum of a narrow linewidth semiconductor laser is applied in the Fourier transform method. The numerical simulation shows that practical gain spectra can be resumed by the Fourier transform method with the deconvolution process. Taking the OSA resolution to be 0.06, 0.1, and 0.2 nm, the gain-reflectivity product spectra with the difference of about 2% are obtained for a 1550-nm semiconductor laser with the cavity length of 720 pm. The spectra obtained by the Fourier transform method without the deconvolution process and the Hakki-Paoli method are presented and compared. The simulation also shows that the Fourier transform method has less sensitivity to noise than the Hakki-Paoli method.

Using Fourier transform infrared grazing incidence reflectivity to study local vibrational modes in GaN

Both Fourier transform infrared (FTIR) grazing incidence reflectivity and FTIR transmission methods have been used to study GaN films grown on alpha-Al2O3 (0001) substrates by atmospheric pressure metal-organic chemical vapor deposition and low pressure metal-organic chemical vapor deposition. The results show that in the frequency range from 400 to 3500 cm(-1) the signal-to-noise ratio of the FTIR grazing incidence measurement is far higher than that of the FTIR transmission measurement. Some new vibrational structures appearing in the former measurement have been discussed. The features around 1460 and 1300 cm(-1) are tentatively assigned to scissoring and wagging local vibrational modes of CH2 in GaN, respectively. (C) 1999 American Institute of Physics. [S0021-8979(99)06509-3].

pessimistic predicate/transform model for long running business processes

Many business processes in enterprise applications are both long running and transactional in nature. However, no current transaction model can provide full transaction support for such long running business processes. This paper proposes a new transaction model, the pessimistic predicate/transform (PP/T) model, which can provide full transaction support for long running business processes. A framework was proposed on the enterprise JavaBeans platform to implement the PP/T model. The framework enables application developers to focus on the business logic, with the underlying platform providing the required transactional semantics. The development and maintenance effort are therefore greatly reduced. Simulations show that the model has a sound concurrency management ability for long running business processes.

Improved digital processing method used for image motion measurement based on hybrid opto-digital joint transform correlator

Hybrid opto-digital joint transform correlator (HODJTC) is effective for image motion measurement, but it is different from the traditional joint transform correlator because it only has one optical transform and the joint power spectrum is directly input into a digital processing unit to compute the image shift. The local cross-correlation image can be directly obtained by adopting a local Fourier transform operator. After the pixel-level location of cross-correlation peak is initially obtained, the up-sampling technique is introduced to relocate the peak in even higher accuracy. With signal-to-noise ratio >= 20 dB, up-sampling factor k >= 10 and the maximum image shift <= 60 pixels, the root-mean-square error of motion measurement accuracy can be controlled below 0.05 pixels.