Results 91 to 100 of about 224,871 (275)
Multi-targets device-free localization based on sparse coding in smart city
International Journal of Distributed Sensor Networks, 2019 With the continuous expansion of the market of device-free localization in smart cities, the requirements of device-free localization technology are becoming higher and higher.
Min Zhao +3 more
doaj +1 more source
Detection of Pitting in Gears Using a Deep Sparse Autoencoder
Applied Sciences, 2017 In this paper; a new method for gear pitting fault detection is presented. The presented method is developed based on a deep sparse autoencoder. The method integrates dictionary learning in sparse coding into a stacked autoencoder network.
Yongzhi Qu +3 more
doaj +1 more source
Learning Word Representations with Hierarchical Sparse Coding [PDF]
, 2014 We propose a new method for learning word representations using hierarchical regularization in sparse coding inspired by the linguistic study of word meanings.
Dyer, Chris +3 more
core
Meniscus Pixel Printing for Contact‐Lens Vision Sensing and Robotic Control
Advanced Functional Materials, EarlyView.A visual‐sensing contact lens is enabled by meniscus pixel printing (MPP), which rapidly patterns a 200 µm perovskite photodetector pixel in 1 s without masks, vacuum processing, or bulky equipment. A deep‐learning‐based super‐resolution reconstructs sparse on‐lens signals into 80 × 80 high‐resolution visual information, while AI‐driven eye‐tracking ...
Byung‐Hoon Gong +7 more
wiley +1 more source
Sparse Sequential Dirichlet Coding
, 2012 This short paper describes a simple coding technique, Sparse Sequential Dirichlet Coding, for multi-alphabet memoryless sources. It is appropriate in situations where only a small, unknown subset of the possible alphabet symbols can be expected to occur ...
Hutter, Marcus, Veness, Joel
core +1 more source
Active Learning‐Accelerated Discovery of Fibrous Hydrogels with Tissue‐Mimetic Viscoelasticity
Advanced Functional Materials, EarlyView.Active learning accelerates the design of fibrous hydrogels that mimic the viscoelasticity of native tissues. By integrating multi‐objective optimization and closed‐loop experimentation, this approach efficiently identifies optimal formulations from thousands of possibilities and decouples elasticity and viscosity. The resulting hydrogels offer tunable
Zhengkun Chen +11 more
wiley +1 more source
KSVD-Based Multiple Description Image Coding
IEEE Access, 2019 In this paper, we present a new multiple description coding scheme, which is based on a sparse dictionary training method called K singular value decomposition (KSVD).
Guina Sun +5 more
doaj +1 more source
Parametric dictionary design for sparse coding [PDF]
, 2009 —This paper introduces a new dictionary design method for sparse coding of a class of signals. It has been shown that one can sparsely approximate some natural signals using an overcomplete set of parametric functions, e.g. [1], [2].
Daudet, L., Davies, M.E., Yaghoobi, M.
core +2 more sources
Sparse Coding with Invariance Constraints [PDF]
, 2003 We suggest a new approach to optimize the learning of sparse features under the constraints of explicit transformation symmetries imposed on the set of feature vectors. Given a set of basis feature vectors and invariance transformations, from each basis feature a family of transformed features is generated.
Heiko Wersing +2 more
openaire +1 more source
Advanced Healthcare Materials, EarlyView.Coagulative granular hydrogels are composed of packed thrombin‐functionalized microgels that catalyze the conversion of fibrinogen into a secondary fibrin network, filling the interstitial voids. This bio‐inspired approach stabilizes the biomaterial to match the robustness of bulk hydrogels without compromising injectability, mimicking the initial ...
Zhipeng Deng +16 more
wiley +1 more source