Results 51 to 60 of about 169,436 (225)

Lorentz violation, Gravity, Dissipation and Holography [PDF]

, 2012
We reconsider Lorentz Violation (LV) at the fundamental level. We show that Lorentz Violation is intimately connected with gravity and that LV couplings in QFT must always be fields in a gravitational sector.
A Dhar, A Kehagias, A Sen, AG Cohen, B Gouteraux, BS Kim, C Burgess, C Charmousis, C Csáki, C Grojean, D Andriot, D Anselmi, D Anselmi, D Blas, D Blas, D Colladay, D Colladay, D Mattingly, DJH Chung, DT Son, E Kiritsis, E Kiritsis, E Kiritsis, E Kiritsis, E Kiritsis, E Kiritsis, E Kiritsis, E Kiritsis, E Kiritsis, E Kiritsis, Elias Kiritsis, G Amelino-Camelia, G Barnich, G Dvali, GD Moore, GR Kalbfleisch, GW Gibbons, H Kleinert, H Osborn, HB Nielsen, I Antoniadis, I Antoniadis, I Antoniadis, I Fuini, J Alspector, J Boer de, J Casalderrey-Solana, J Casalderrey-Solana, J Collins, J Iliopoulos, J Khoury, J McGreevy, JD Jackson, JM Cornwall, JP Derendinger, JW Elliott, KR Dienes, M Baggio, M Jarvinen, M Mucha-Kruczynski, M Nagano, M Porrati, M Smiciklas, MJ Duff, MJ Longo, N Arkani-Hamed, N Arkani-Hamed, N Arkani-Hamed, N Seiberg, O Pujolàs, P Adamson, P Anastasopoulos, P Hořava, P Hořava, P Kraus, R Bluhm, R Brustein, R Casero, RC Myers, S Chadha, S Deser, S Groot Nibbelink, S Kachru, S Mukohyama, S Mukohyama, SHS Alexander, SR Coleman, SR Coleman, SS Gubser, SS Gubser, T Adam, T Faulkner, T Griffin, T Jacobson, U Gürsoy, U Gürsoy, VA Kostelecky, VA Kostelecky, W Chemissany   +98 more
core   +4 more sources

Parallelizing Scale Invariant Feature Transform on a Distributed Memory Cluster [PDF]

, 2011
Scale Invariant Feature Transform (SIFT) is a computer vision algorithm that is widely-used to extract features from images. We explored accelerating an existing implementation of this algorithm with message passing in order to analyze large data sets ...
Bobovych, Stanislav
core   +2 more sources

A Full-Featured FPGA-Based Pipelined Architecture for SIFT Extraction

IEEE Access, 2021
Image feature detection is a key task in computer vision. Scale Invariant Feature Transform (SIFT) is a prevalent and well known algorithm for robust feature detection.
Philipp Kreowsky, Benno Stabernack
doaj   +1 more source

Rotation and Scale Invariant Texture Classification [PDF]

, 2008
Texture classification is very important in image analysis. Content based image retrieval, inspection of surfaces, object recognition by texture, document segmentation are few examples where texture classification plays a major role.
Agarwal, Anubhav, Manohar, Madhukar
core  

Linear Spatial Pyramid Matching Using Non-convex and non-negative Sparse Coding for Image Classification

, 2015
Recently sparse coding have been highly successful in image classification mainly due to its capability of incorporating the sparsity of image representation.
Bao, Chengqiang, He, Liangtian, Wang, Yilun   +2 more
core   +1 more source

Improved SIFT algorithm for place categorization [PDF]

, 2015
The main aim of this paper is an improvement of the famous Scale Invariant Feature Transform (SIFT) algorithm used in place categorization. Masking approach to reduce the computational complexity of SIFT have been proposed.
Ahmad, Siti Anom, Marhaban, Mohammad Hamiruce, Ramli, Abd Rahman, Said, Yunusa Ali   +3 more
core   +1 more source

A Zero-Watermarking Algorithm Based on Scale-Invariant Feature Reconstruction Transform

Applied Sciences
In order to effectively protect and verify the copyright information of multimedia digital works, this paper proposes a zero-watermarking algorithm based on carrier image feature point descriptors.
Fan Li, Zhong-Xun Wang
doaj   +1 more source

Learning Robust Feature Descriptor for Image Registration With Genetic Programming

IEEE Access, 2020
The robustness and accuracy of feature descriptor are two essential factors in the process of image registration. Existing feature descriptors can extract important image features, but it may be difficult to find enough correct correspondences for ...
Yue Wu, Qingxiu Su, Wenping Ma, Shaodi Liu, Qiguang Miao   +4 more
doaj   +1 more source

Person Re-identification by Local Maximal Occurrence Representation and Metric Learning [PDF]

, 2015
Person re-identification is an important technique towards automatic search of a person's presence in a surveillance video. Two fundamental problems are critical for person re-identification, feature representation and metric learning.
Hu, Yang, Li, Stan Z., Liao, Shengcai, Zhu, Xiangyu   +3 more
core   +1 more source

Robust Descriptor Algorithm Considering the Changing Gray Value Trends Inside Ground Objects for Heterogeneous Optical Image Matching

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
Differences in sensor types, resolutions, and imaging conditions can lead to considerable spectral differences in heterogeneous optical remote sensing images and the similarity of scale-invariant feature transform (SIFT) or local self-similarities (LSS ...
Li Xue, Yehua Sheng, Ka Zhang
doaj   +1 more source