Simulation results indicate that both estimators are able to achieve great performance regardless of the measurement error level.
Automatic machine translation made its appearance a long time ago, but deep learning has achieved great performance in two aspects: automatic translation of words and words in images.
By making use of the second order differential filtering and subspace method, the proposed algorithm achieves great performance improvement with reduced complexity.
Recent advances [26] in deep learning application, such as computer simultaneous interpretation by Microsoft, have proven that deep learning is feasible in many machine learning tasks and can achieve great performance, so that more and more experts from the AI area believe that deep learning gives machine learning the second wave.
In the experiments, the proposed framework has achieved great performance for face recognition and verification with high speed and high accuracy, based on the public available datasets such as the Labeled Face in the Wild dataset and the AT&T database of faces.
Turbo principle was originated from turbo decoding, and in the context of cooperative communication systems, it explores the synergy from distributed detections on symbols and combines the soft (probabilistic) detection in a turbo fashion to achieve greater performance improvement.
Evaluation on several face databases and the experimental results demonstrate that these proposed classifiers can achieve greater performance than the C-PtP based 1-NNs and competitive recognition accuracy and robustness compared with the state-of-the-art classifiers.
In this paper, we exploit the expressiveness of Gamma to elegantly and succinctly specify the normalization aspects in relational databases and use its computational power to achieve greater performance in verifying and realizing relational database normal forms.
Our findings indicate that the scheme consistently achieves greater performance improvement on Erdos Renyi's random graphs than on other graphs such as Barabasi-Albert's scale-free graphs and two social graphs empirically sampled from Facebook and Douban OSNs.
But we can reasonably expect to see new opportunities emerge based on AI's ability to take over non-value tasks and enhance individual capabilities to, in turn, achieve greater performance and results".
