|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Simplex and duplex PCR assays for species specific identification of cattle and buffalo milk and cheese显示文摘 | Sachinandan De Biswajit Brahma Shamik Polley Ayan Mukherjee Deepak Banerjee Moloya Gohaina Karan Pratap Singh Rameswar Singh Tirtha Kumar Datta Surender Lal Goswami | 2010 | Food Control2010，，5： | 1 |
| 2 | An efficient support vector machine learning method with second-order cone programming for large-scale problem显示文摘 | Masakazu Muramatsu Haruhisa Takahashi | 2005 | Applied Intelligence2005，23，3： | 1 |
| 3 | An efficient support vector machine learning method with second - order cone programming for large - scale problem显示文摘 | Rameswar Dehnath Masakazu Muramatsu Haruhisa Takahashi | 2005 | Applied Intelligence2005，23，3： | 1 |
| 4 | Genetic Dissection of Grain Size Traits Through Genome-Wide Association Study Based on Genic Markers in Rice显示文摘Grain size plays a significant role in rice,starting from affecting yield to consumer preference,which is the driving force for deep investigation and improvement of grain size characters.Quantitative inheritance makes these traits complex to breed on account of several alleles contributing to the complete trait expression.We employed genome-wide association study in an association panel of 88 rice genotypes using 142 new candidate gene based SSR(cgSSR)markers,derived from yield-related candidate genes,with the efficient mixed-model association coupled mixed linear model for dissecting complete genetic control of grain size traits.A total of 10 significant associations were identified for four grain size-related characters(grain weight,grain length,grain width,and length-width ratio).Among the identified associations,seven marker trait associations explain more than 10%of the phenotypic variation,indicating major putative QTLs for respective traits.The allelic variations at genes OsBC1L4,SHO1 and OsD2 showed association between 1000-grain weight and grain width,1000-grain weight and grain length,and grain width and length-width ratio,respectively.The cgSSR markers,associated with corresponding traits,can be utilized for direct allelic selection,while other significantly associated cgSSRs may be utilized for allelic accumulation in the breeding programs or grain size improvement.The new cgSSR markers associated with grain size related characters have a significant impact on practical plant breeding to increase the number of causative alleles for these traits through marker aided rice breeding programs. | Amrit Kumar NAYAK Anilkumar C Sasmita BEHERA Rameswar Prasad SAH Gera Roopa LAVANYA Awadhesh KUMAR Lambodar BEHERA Muhammed Azharudheen TP | 2022 | Rice science2022，29，5： | 0 |
| 5 | An Improved Encoder-Decoder CNN with Region-Based Filtering for Vibrant Colorization显示文摘Colorization is the practice of adding appropriate chromatic values to monochrome photographs or videos.A real-valued luminance image can be mapped to a three-dimensional color image.However,it is a severely ill-defined problem and not has a single solution.In this paper,an encoder-decoder Convolutional Neural Network(CNN)model is used for colorizing gray images where the encoder is a Densely Connected Convolutional Network(DenseNet)and the decoder is a conventional CNN.The DenseNet extracts image features from gray images and the conventional CNN outputs a^(*)b^(*)color channels.Due to a large number of desaturated color components compared to saturated color components in the training images,the saturated color components have a strong tendency towards desaturated color components in the predicted a^(*)b^(*)channel.To solve the problems,we rebalance the predicted a^(*)b^(*)color channel by smoothing every subregion individually using the average filter.2 stage k-means clustering technique is applied to divide the subregions.Then we apply Gamma transformation in the entire a^(*)b^(*)channel to saturate the image.We compare our proposed method with several existing methods.From the experimental results,we see that our proposed method has made some notable improvements over the existing methods and color representation of gray-scale images by our proposed method is more plausible to visualize.Additionally,our suggested approach beats other approaches in terms of Peak Signal-to-Noise Ratio(PSNR),Structural Similarity Index Measure(SSIM)and Histogram. | Mrityunjoy Gain Md Arifur Rahman Rameswar Debnath MrimMAlnfiai Abdullah Sheikh Mehedi Masud Anupam Kumar Bairagi | 2023 | Computer Systems Science & Engineering2023，46，7： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员