Dynamics reconstruction and classification via Koopman features
نویسندگان
چکیده
منابع مشابه
Improving Classification via Reconstruction
Learning a many-parameter model is generally an under-constrained problem that requires additional regularization. We propose to use reconstruction as a regularization constraint for image classification. We show that fusing the two models together is an effective regularizer which adds to the improvement achieved by weight decay constraints. This regularization is effective for single networks...
متن کاملHyperspectral Images Classification by Combination of Spatial Features Based on Local Surface Fitting and Spectral Features
Hyperspectral sensors are important tools in monitoring the phenomena of the Earth due to the acquisition of a large number of spectral bands. Hyperspectral image classification is one of the most important fields of hyperspectral data processing, and so far there have been many attempts to increase its accuracy. Spatial features are important due to their ability to increase classification acc...
متن کاملVisual Event Classification via Force Dynamics
This paper presents an implemented system, called LEONARD, that classifies simple spatial motion events, such as pick up and put down, from video input. Unlike previous systems that classify events based on their motion profile, LEONARD uses changes in the state of force-dynamic relations, such as support, contact, and attachment, to distinguish between event types. This paper presents an overv...
متن کاملGender classification via lips: static and dynamic features
Automatic gender classification has many security and commercial applications. Various modalities have been investigated for gender classification with face-based classification being the most popular. In some real-world scenarios the face may be partially occluded. In these circumstances a classification based on individual parts of the face known as local features must be adopted. We investig...
متن کاملStudy of dynamics in unsteady flows using Koopman mode decomposition
The Koopman Mode Decomposition (KMD) is a data-analysis technique which is often used to extract the spatio-temporal patterns of complex flows. In this paper, we use KMD to study bifurcations of the lid-driven flow in a two-dimensional square cavity based on rigorous theorems related to the spectrum of the Koopman operator. We adopt a new computational algorithm, which is capable of detecting t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Data Mining and Knowledge Discovery
سال: 2019
ISSN: 1384-5810,1573-756X
DOI: 10.1007/s10618-019-00639-x