6,302 research outputs found
Bayesian Reconstruction of Approximately Periodic Potentials at Finite Temperature
The paper discusses the reconstruction of potentials for quantum systems at
finite temperatures from observational data. A nonparametric approach is
developed, based on the framework of Bayesian statistics, to solve such inverse
problems. Besides the specific model of quantum statistics giving the
probability of observational data, a Bayesian approach is essentially based on
"a priori" information available for the potential. Different possibilities to
implement "a priori" information are discussed in detail, including
hyperparameters, hyperfields, and non--Gaussian auxiliary fields. Special
emphasis is put on the reconstruction of potentials with approximate
periodicity. The feasibility of the approach is demonstrated for a numerical
model.Comment: 18 pages, 17 figures, LaTe
Deep Image Retrieval: A Survey
In recent years a vast amount of visual content has been generated and shared
from various fields, such as social media platforms, medical images, and
robotics. This abundance of content creation and sharing has introduced new
challenges. In particular, searching databases for similar content, i.e.content
based image retrieval (CBIR), is a long-established research area, and more
efficient and accurate methods are needed for real time retrieval. Artificial
intelligence has made progress in CBIR and has significantly facilitated the
process of intelligent search. In this survey we organize and review recent
CBIR works that are developed based on deep learning algorithms and techniques,
including insights and techniques from recent papers. We identify and present
the commonly-used benchmarks and evaluation methods used in the field. We
collect common challenges and propose promising future directions. More
specifically, we focus on image retrieval with deep learning and organize the
state of the art methods according to the types of deep network structure, deep
features, feature enhancement methods, and network fine-tuning strategies. Our
survey considers a wide variety of recent methods, aiming to promote a global
view of the field of instance-based CBIR.Comment: 20 pages, 11 figure
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