In this study, an improved end-to-end framework for instance segmentation of military camouflaged targets, referred to as MilInst, is proposed. The builds upon SparseInst method developed by Cheng et al . [27]. Several improvements are introduced enhance the model’s performance. First, Receptiv...

Abstract Recognizing 3D part instances from a point cloud is crucial for structure and scene understanding. Several learning-based approaches use semantic segmentation instance center prediction as training tasks fail to further exploit the inherent relationship between shape semantics instances. In this paper, we present new method segmentation. Our exploits fuse nonlocal features, such predic...

Pension buy-ins and buy-outs have become an important aspect of managing pension risk in recent years. As a step toward understanding these pension de-risking instruments, we develop models for pricing investment risk and longevity risk embedded in pension buy-ins and buy-outs. We also bring a contingent-claims framework to price credit risk of buy-in bulk annuities. Overall, our model can be u...

We briefly review data analysis of the Island order book, part of NASDAQ, which suggests a framework to which all limit order market models should comply. Using a simple exclusion particle model, we argue that short-time price over-diffusion in limit order markets is due to the non-equilibrium of order placement, cancellation and execution rates, which is an inherent feature of real limit order...

This paper deals with the issue of buy-in thresholds in portfolio optimization using the Markowitz approach. Optimal values of invested fractions calculated using, for instance, the classical minimum-risk problem can be unsatisfactory in practice because they imply that very small amounts of certain assets are purchased. Realistically, we want to impose a discrete restriction on each invested f...