Results 71 to 80 of about 572,458 (282)

STUDENT’S ATTITUDE TOWARDS DICTIONARY AND ITS USAGE : A Case of Study for English Department Students Diponegoro University [PDF]

, 2016
In learning a foreign language, dictionary is one of learning aids to assist students in making decision about making sense of words in usage –in the target language. This research is conducted to discover how English Department students in Universitas
Candra, Calvin, Davin P, Nathaniel, Ersaa M, Aswit., Prihantoro, Prihantoro   +3 more
core  

Image Super-Resolution via Dual-Dictionary Learning And Sparse Representation

, 2012
Learning-based image super-resolution aims to reconstruct high-frequency (HF) details from the prior model trained by a set of high- and low-resolution image patches.
Ma, Siwei, Xiong, Ruiqin, Zhang, Jian, Zhao, Chen, Zhao, Debin   +4 more
core   +1 more source

Automatically Defining Protein Words for Diverse Functional Predictions Based on Attention Analysis of a Protein Language Model

Advanced Science, EarlyView.
Understanding protein sequence–function relationships remains challenging due to poorly defined motifs and limited residue‐level annotations. An annotation‐agnostic framework is introduced that segments protein sequences into “protein words” using attention patterns from protein language models.
Hedi Chen, Jingrui Zhong, Xiaochun Zhang, Jingke Chen, Lin Guo, Xiaoliang Xiong, Xiaonan Zhang, Xiangyu Liu, Bailong Xiao, Boxue Tian   +9 more
wiley   +1 more source

Supervised Dictionary Learning

, 2008
It is now well established that sparse signal models are well suited to restoration tasks and can effectively be learned from audio, image, and video data. Recent research has been aimed at learning discriminative sparse models instead of purely reconstructive ones.
Mairal, Julien, Bach, Francis, Ponce, Jean, Sapiro, Guillermo, Zisserman, Andrew   +4 more
openaire   +4 more sources

Effective Input Projection for Updating Dictionary Atoms in Sparse Coding-Based Image Denoising

IEEE Access
Adaptive dictionary learning algorithms offer enhanced performance through the joint optimization of dictionary atoms and sparse representations.
Ammar Hoori, Alex J. Aved, Simegnew Yihunie Alaba, Yuichi Motai   +3 more
doaj   +1 more source

An Analysis Dictionary Learning Algorithm under a Noisy Data Model with Orthogonality Constraint

The Scientific World Journal, 2014
Two common problems are often encountered in analysis dictionary learning (ADL) algorithms. The first one is that the original clean signals for learning the dictionary are assumed to be known, which otherwise need to be estimated from noisy measurements.
Ye Zhang, Tenglong Yu, Wenwu Wang
doaj   +1 more source

Solving Inverse Problems in Imaging via Deep Dictionary Learning

IEEE Access, 2019
In dictionary learning-based inversion, the dictionary and coefficients are learnt adaptively from the image during the inversion process; this is a shallow approach since one layer of the dictionary is learnt.
John Lewis D., Vanika Singhal, Angshul Majumdar   +2 more
doaj   +1 more source

Dictionary Learning for Blind One Bit Compressed Sensing

, 2015
This letter proposes a dictionary learning algorithm for blind one bit compressed sensing. In the blind one bit compressed sensing framework, the original signal to be reconstructed from one bit linear random measurements is sparse in an unknown domain ...
Korki, Mehdi, Marvasti, Farrokh, Zayyani, Hadi   +2 more
core   +1 more source

opXRD: Open Experimental Powder X‐Ray Diffraction Database

Advanced Intelligent Discovery, EarlyView.
We introduce the Open Experimental Powder X‐ray Diffraction Database, the largest openly accessible collection of experimental powder diffractograms, comprising over 92,000 patterns collected across diverse material classes and experimental setups. Our ongoing effort aims to guide machine learning research toward fully automated analysis of pXRD data ...
Daniel Hollarek, Henrik Schopmans, Jona Östreicher, Jonas Teufel, Bin Cao, Adie Alwen, Simon Schweidler, Mriganka Singh, Tim Kodalle, Hanlin Hu, Gregoire Heymans, Maged Abdelsamie, Arthur Hardiagon, Alexander Wieczorek, Siarhei Zhuk, Ruth Schwaiger, Sebastian Siol, François‐Xavier Coudert, Moritz Wolf, Carolin M. Sutter‐Fella, Ben Breitung, Andrea M. Hodge, Tong‐yi Zhang, Pascal Friederich   +23 more
wiley   +1 more source

Dictionary Learning of Symmetric Positive Definite Data Based on Riemannian Manifold Tangent Spaces and Local Homeomorphism

IEEE Access, 2022
Symmetric Positive Definite (SPD) data are increasingly prevalent in dictionary learning recently. SPD data are the typical non-Euclidean data and cannot constitute a Euclidean space.
Hui He, Shuyu Liu, Zhengming Ma, Weijia Feng   +3 more
doaj   +1 more source