Zobrazeno 1 - 10
of 68
pro vyhledávání: '"Long, Zhiling"'
Publikováno v:
Applied Computing and Intelligence, vol. 1, no. 1, pp. 31-45, Nov. 2021
A new approach to seismic interpretation is proposed to leverage visual perception and human visual system modeling. Specifically, a saliency detection algorithm based on a novel attention model is proposed for identifying subsurface structures withi
Externí odkaz:
http://arxiv.org/abs/2201.06174
Autor:
Hu, Yuting, Long, Zhiling, Sundaresan, Anirudha, Alfarraj, Motaz, AlRegib, Ghassan, Park, Sungmee, Jayaraman, Sundaresan
Tactile sensing or fabric hand plays a critical role in an individual's decision to buy a certain fabric from the range of available fabrics for a desired application. Therefore, textile and clothing manufacturers have long been in search of an objec
Externí odkaz:
http://arxiv.org/abs/2003.07725
In this paper, we propose a multi-level texture encoding and representation network (MuLTER) for texture-related applications. Based on a multi-level pooling architecture, the MuLTER network simultaneously leverages low- and high-level features to ma
Externí odkaz:
http://arxiv.org/abs/1905.09907
Publikováno v:
Proceedings of IEEE International Conference on Image Processing (ICIP), Beijing, China, Sep. 2017
In this paper, we propose a novel approach for saliency detection for seismic applications using 3D-FFT local spectra and multi-dimensional plane projections. We develop a projection scheme by dividing a 3D-FFT local spectrum of a data volume into th
Externí odkaz:
http://arxiv.org/abs/1901.11095
In this paper, we present an analysis of recorded eye-fixation data from human subjects viewing video sequences. The purpose is to better understand visual attention for videos. Utilizing the eye-fixation data provided in the CRCNS (Collaborative Res
Externí odkaz:
http://arxiv.org/abs/1901.10957
Autor:
Long, Zhiling, Alaudah, Yazeed, Qureshi, Muhammad Ali, Farraj, Motaz Al, Wang, Zhen, Amin, Asjad, Deriche, Mohamed, AlRegib, Ghassan
Publikováno v:
Proceedings of the SEG 85th Annual Meeting, New Orleans, LA, Oct. 2015
In this paper, we examine several typical texture attributes developed in the image processing community in recent years with respect to their capability of characterizing a migrated seismic volume. These attributes are generated in either frequency
Externí odkaz:
http://arxiv.org/abs/1901.10909
Publikováno v:
The Leading Edge 37.6 (2018): 443-450
We explore the use of multiresolution analysis techniques as texture attributes for seismic image characterization, especially in representing subsurface structures in large migrated seismic data. Namely, we explore the Gaussian pyramid, the discrete
Externí odkaz:
http://arxiv.org/abs/1901.08539
In this paper, we propose a saliency-based attribute, SalSi, to detect salt dome bodies within seismic volumes. SalSi is based on the saliency theory and modeling of the human vision system (HVS). In this work, we aim to highlight the parts of the se
Externí odkaz:
http://arxiv.org/abs/1901.02937
Publikováno v:
Proceedings of IEEE ICIP 2015, Quebec City, Canada, Sep. 2015
The exploration of petroleum reservoirs has a close relationship with the identification of salt domes. To efficiently interpret salt-dome structures, in this paper, we propose a method that tracks salt-dome boundaries through seismic volumes using a
Externí odkaz:
http://arxiv.org/abs/1901.02921
Publikováno v:
IEEE Transactions on Image Processing, vol. 27, no. 6, pp. 2818-2827, Jun. 2018
In this paper, we address the problem of quantifying reliability of computational saliency for videos, which can be used to improve saliency-based video processing and enable more reliable performance and risk assessment of such processing. Our appro
Externí odkaz:
http://arxiv.org/abs/1901.01550