Furthermore, BrainGNN uses ROI-selection layer pooling (R-pool ... ideal for analyzing complex brain imaging data linked with ASD. The Transformer design includes an encoder-decoder structure, however ...

Abstract: The efficient and accurate detection of the mechanical structure and insulation condition of transformer windings is a key prerequisite for condition assessment and maintenance. However, an ...

The stratum corneum often is described as having a brick-and-mortar type of structure. In this analogy, the "bricks" are corneocytes, which originate in the deepest layer of the epidermis, the stratum ...

The Transformer deep neural network architecture ... text by jointly conditioning on both left and right context in all layers. The two model sizes initially used were 100 million and 340 million ...

Please calibrate the camera(s) with the robot before data collection and evaluation to ensure correct spatial transformations between camera(s) and the robot. Please refer to calibration guide for ...

The attack by a Russian drone has damaged the outer layer of the New Safe Confinement (NSC ... a Russian attack drone equipped with a high-explosive warhead struck the Shelter structure over the ...

Despite architectural similarities between modern transformers and deep residual networks, where layer depth can sometimes be redundant, research has yet to explore these redundancies to fully ...

Initially, a bilayer targeted prediction method is proposed to strengthen gradient interaction across decoder layers ... The pyramid structure and self-attention mechanism from pyramid vision ...