Experiments on different challenging video sequences demonstrate that the proposed tracker performs favorably against several state-of-the-art trackers.
Numerous experiments with state-of-the-art algorithms on challenging sequences demonstrate that the proposed algorithm performs well in terms of accuracy and stability.
Extensive experimental results on different video sequences demonstrate that the proposed method performs favorably for detection and tracking compared with baseline methods in terms of efficiency and accuracy.
Experimental results over a collection of public and own datasets of real image sequences demonstrate that the proposed technique achieves a superior performance compared with state-of-the-art methods.
The experiments conducted on representative test video sequences demonstrate that the proposed method provides promising results and is competitive with other state-of-the-art denoising techniques both in terms of objective metric and in perceptual quality.
Experimental results conducted on various sequences demonstrate that the proposed frame rate reduction is able to significantly improve the quality of up-sampled frames compared with other down-sampling methods.
Experimental results on three sequences demonstrate that the proposed small target detection method can not only suppress background clutter effectively even if with strong noise interference, but also detect targets accurately with low false alarm rate and high speed.
Peptide truncation experiments showed FEI to be the minimal binding sequence within the DLFEIFEIER sequence, and adhesion experiments with peptides that include both the RGD and FEI sequences demonstrate that the two peptides bind synergistically to the receptor.
