AbstractSequence-to-Sequence (S2S) models have achieved remarkable success on various text generation tasks.However, learning complex structures with S2S models remains challenging as external neural modules and additional lexicons are often supplemented to predict non-textual outputs.We present a systematic study of S2S modeling using contained tr
A method to deduce the characteristics of rail corrugation was developed and presented in this paper.It has been found that noise and vibration in the train vehicle were primarily contributed by rail corrugation and wheel polygonalisation.As the characteristics of wheel sets of a particular train can be assumed to be unchanged trufel ultra during a
Accurate depth information is crucial for various computer vision applications such as augmented reality, 3D modeling, and autonomous vehicles.Recent advancements have significantly improved both supervised and self-supervised methods for depth estimation.However, most current approaches primarily focus on monocular depth estimation and face challe