We propose an end-to-end Multitask Learning Transformer framework, named MulT, to simultane-ously learn multiple high-level vision tasks, including depth estimation, semantic segmentation, reshading, …

To address the above issues, in this paper we propose the Multimodal Transformer (MulT), an end-to-end model that extends the standard Trans-former network (Vaswani et al., 2017) to learn rep …

The electric multipole expansion is a useful tool for calculating the Coulomb potential Φ(x) (and hence the electric field E(x)) due to some compact charge system at long distances from that system, |x| ≫ …

In this paper, we introduce a wearable Mechanical Upper Limbs-Tracker (MULT), shown in Fig. 1, designed for accurate tracking the hands dorsum for telemanipulation applications. Vision-based …

V V 3 (v; w) 7!v w 2 R space of Vn to U. We will denote it by Mult(V1 Vn; U) = Multn(V1 Vn; U) that these are n-linear maps). This space, Mult(V1 Vn; U), is a vector space: any linear combination of two n …

ractitioners waste a ton of resources on redundant training [1]. By being a multitask framework, our MulT model helps to reduce the power con-sumption during inference unlike the single task baselines that …

Franklin Multisector Income ETF (MULT) Multi-Sector | Factsheet as of September 30, 2025