Amino acid classification based on their dipole and side chain volumes.

Amino acid classification based on their dipole and side chain volumes.</p

Adjusting the learning rate of our model.

Adjusting the learning rate of our model.</p

Neural network training procedure.

Neural network training procedure.</p

Results based on DNN with CT, AC, LD, and MOS on the benchmark dataset.

Results based on DNN with CT, AC, LD, and MOS on the benchmark dataset.</p

Adjusting of the network width of our model.

Adjusting of the network width of our model.</p

Comparison of the performances of MOS based on different classifiers using the human dataset.

Comparison of the performances of MOS based on different classifiers using the human dataset.</p

Results based on DNN with CT, AC, LD, and MOS on the benchmark dataset.

Results based on DNN with CT, AC, LD, and MOS on the benchmark dataset.</p

Adjusting the network width of our model.

Adjusting the network width of our model.</p

Results of DNN with different feature extraction method on a non-redundant dataset.

Results of DNN with different feature extraction method on a non-redundant dataset.</p

Experiment with weakly light, de-hazy and de-rain images.

Experiment with weakly light, de-hazy and de-rain images.</p