Sentence examples for databases demonstrate that from inspiring English sources
Experiments on the MNIST and CIFAR-10 databases demonstrate that the proposed approaches are comparable with state-of-the-art deep learning architectures in the literature.
The experimental results on six face recognition databases and two object recognition databases demonstrate that the proposed methods outperform the competitors used in the experiments.
Moreover, the results obtained on three standard face databases demonstrate that SVDP-SRC is quite effective to handle the SSS problems in terms of recognition accuracy.
Experimental results on three benchmark face databases demonstrate that our proposed ASFDA is superior to some state-of-the-art methods.
Extensive experiments performed on three types of palmprint databases demonstrate that the proposed approach has excellent performance in comparison with previously proposed state-of-the-art approaches.
Extensive experimentations on the AR, Extended Yale B and CMU Multi-PIE databases demonstrate that PFSR-based classification method is competitive and robust for insufficient training samples FR problem.
Comparison of the nucleotide and amino acid sequences with Genebank databases demonstrated that the beta toxin of C. haemolyticum exhibits high homology with other bacterial PLPCs.
In addition, an evaluation on three databases demonstrates that increase in the computational time of the proposed method was sublinear when the number of subjects in the gallery increased.
Analysis of the wheat DNA sequences available in databases demonstrated that Fatima elements are present in all the three genomes (A, B, and D) of common wheat.
Our experimental results on Waveform and Handwritten Digits database demonstrate that SDBSkeletonization improves the overall classification performance.
