271 research outputs found
H\"older Error Bounds and H\"older Calmness with Applications to Convex Semi-Infinite Optimization
Using techniques of variational analysis, necessary and sufficient
subdifferential conditions for H\"older error bounds are investigated and some
new estimates for the corresponding modulus are obtained. As an application, we
consider the setting of convex semi-infinite optimization and give a
characterization of the H\"older calmness of the argmin mapping in terms of the
level set mapping (with respect to the objective function) and a special
supremum function. We also estimate the H\"older calmness modulus of the argmin
mapping in the framework of linear programming.Comment: 25 page
Analysis of Reverse Logistics Management in China
With the global market competition becoming fierce, there is increasing concern regarding sustainable development strategy. The notion of sustainable development makes reverse logistics recognized. Reverse Logistics has recently received growing attention all over the world, and many enterprises have begun to regard it as a streamlined business strategy to gain economic benefits and maximize recovery value, to reduce waste and minimize cost, and to improve the corporate image and increase market share. While most local Chinese enterprises are familiar with forward logistics activities, the notion of reverse logistics is relatively new for many Chinese companies currently, or it is simply regarded as waste management. Although the related research on China's reverse logistics management is in infancy, it has become a crucial research topic in the current sustainable economy strategy development in China
Modeling Human Performance on Statistical Word Segmentation Tasks
Harnessing the orbital angular momentum (OAM) of light is an appealing approach to developing photonic technologies for future applications in optical communications and high-dimensional quantum key distribution (QKD) systems. An outstanding challenge to the widespread uptake of the OAM resource is its efficient generation. In this work we design a new device that can directly emit an OAM-carrying light beam from a low-cost semiconductor laser. By fabricating micro-scale spiral phase plates within the aperture of a vertical-cavity surface-emitting laser (VCSEL), the linearly polarized Gaussian beam emitted by the VCSEL is converted into a beam carrying specific OAM modes and their superposition states, with high efficiency and high beam quality. This new approach to OAM generation may be particularly useful in the field of OAM-based optical and quantum communications, especially for short-reach data interconnects and QKD
ZoomNeXt: A Unified Collaborative Pyramid Network for Camouflaged Object Detection
Recent camouflaged object detection (COD) attempts to segment objects
visually blended into their surroundings, which is extremely complex and
difficult in real-world scenarios. Apart from the high intrinsic similarity
between camouflaged objects and their background, objects are usually diverse
in scale, fuzzy in appearance, and even severely occluded. To this end, we
propose an effective unified collaborative pyramid network which mimics human
behavior when observing vague images and videos, \textit{i.e.}, zooming in and
out. Specifically, our approach employs the zooming strategy to learn
discriminative mixed-scale semantics by the multi-head scale integration and
rich granularity perception units, which are designed to fully explore
imperceptible clues between candidate objects and background surroundings. The
former's intrinsic multi-head aggregation provides more diverse visual
patterns. The latter's routing mechanism can effectively propagate inter-frame
difference in spatiotemporal scenarios and adaptively ignore static
representations. They provides a solid foundation for realizing a unified
architecture for static and dynamic COD. Moreover, considering the uncertainty
and ambiguity derived from indistinguishable textures, we construct a simple
yet effective regularization, uncertainty awareness loss, to encourage
predictions with higher confidence in candidate regions. Our highly
task-friendly framework consistently outperforms existing state-of-the-art
methods in image and video COD benchmarks. The code will be available at
\url{https://github.com/lartpang/ZoomNeXt}.Comment: Extensions to the conference version: arXiv:2203.02688; Fixed some
word error
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