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Articles by J. Tan
Total Records ( 3 ) for J. Tan
  X. M. Fan , H. M. Chen , J. Tan , C. X. Xu , Y. M. Zhang , Y. X. Huang and M. S. Kang
  New heterotic groups are needed for increasing genetic diversity and productivity in maize (Zea mays L.). A study was conducted with the following objectives: (i) to determine if exotic tropical maize germplasm (TRMG) can increase diversity of Chinese maize germplasm for grain yield and five yield component traits (YCTs), namely, ear length (EL), ear diameter (ED), number of kernel rows per ear (RE), number of kernels per row (KR), and 1000-kernel weight (TKW), and (ii) to estimate general combining ability (GCA) and specific combining ability (SCA) effects to identify a possible new heterotic pattern. Twenty-five temperate maize germplasm (TEMG) from both China and the United States were crossed with four TRMG from the International Maize and Wheat Improvement Center (CIMMYT). The 100 testcrosses were evaluated in field trials for grain yield and five YCTs at three locations in Yunnan, China. Tropical lines YML146 and YML145 showed, in crosses with most of the TEMG, significant positive SCA effects for grain yield and most of the YCTs, indicating that these lines had a different genetic base from that of TEMG and could increase genetic diversity of Chinese maize germplasm. The GCA effects were more important and reliable than SCA effects for heterotic pattern classification. Exotic line YML146 (derived from Suwan1) was identified as a new heterotic group, different from Reid, Lancaster, Tangsipingtou (TSPT), and Luda Red Cob (LDRC). A new heterotic pattern of temperate x Suwan1 was postulated, which could be as important as the widely accepted flint x dent heterotic pattern.
  Md. Atiqur Rahman Ahad , J. Tan , H. Kim and S. shikawa
  Problem statement: In template-based motion recognition approaches, feature sets are computed from the template for classification. Hu invariants are widely employed for this purpose since its inception. However, development of lower-dimensional feature vector sets is required for faster computation along with robust recognition. The concept of reduced size of Hu moment is really interesting. From its inception, seven higher orders Hu moments have been employed by many researchers without considering why seven and why not less numbers. Approach: In this study, we analyzed with various feature sets with different number of Hu moments and rationalized that based on the characteristics of central moments, it is not necessary to employ all the seven moments in every applications and, in that way, we can reduce the computational cost and make it faster. Results: Based on various feature vectors sets, it is evident that we can use lower dimensional feature vectors for our Directional Motion History Image (DMHI) method and other methods. Conclusion: Therefore, we can conclude that we do not need all seven invariants, rather 1st two or three invariants seem enough-as we are not reproducing the image. Higher invariants are noisy and hence can be ignored. The 0th order moment for Energy images provide enough information about the mass area and hence, no need to calculate the other seven invariants.
  X. Sun , Z. Chen , Y. Li , L. Liao and J. Tan
  Not avialable
 
 
 
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