Neural machine translation (NMT) is a recent and effective technique which led to remarkable improvements in comparison of conventional machine translation techniques.
Semi-parametric survival analysis methods like the Cox Proportional Hazards (CPH) regression (Cox, 1972) are a popular approach for survival analysis.
In the recent time deep learning has achieved huge popularity due to its performance in various machine learning algorithms.
Contact-rich manipulation tasks in unstructured environments often require both haptic and visual feedback.
Our model jointly estimates (i) the segmentation of the scene into an unknown but finite number of objects, (ii) the motion trajectories of these objects and (iii) the object scene flow.
We have also discussed about how the advancement in the task of object recognition and machine translation has greatly improved the performance of image captioning model in recent years.