A hybrid optical/digital correlator filter synthesis architecture for distortion-invariant pattern recognition and scene analysis is described. Distortion-invariant correlation filter synthetic discriminant function d...
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The problem of recognition of objects in images is investigated from the simultaneous viewpoint of image bandwidth compression and automatic target recognition. A hypothetical scenario is suggested in which recognitio...
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The problem of recognition of objects in images is investigated from the simultaneous viewpoint of image bandwidth compression and automatic target recognition. A hypothetical scenario is suggested in which recognition is implemented on features in the block cosine transform domain which is useful for data compression as well. Useful features from this cosine domain are developed based upon correlation parameters and homogeneity measures which appear to discriminate successfully between natural and man-made objects. The Bhattacharyya feature discriminator is used to provide a 10:1 compression of the feature space for implementation of simple statistical decision surfaces (Gaussian classification).
作者：
BECKER, LOUIS A.SIEGRIST, FRANKLIN I.Louis A. Becker was born in New Rochelle
N.Y. in 1930 receiving his earlier education in the New Rochelle Public Schools. He completed his undergraduate studies at Manhattan College in 1952 receiving his BCE degree during which time he was also engaged in land surveying. Following this he did postgraduate study at Virginia Polytechnic Institute obtaining his MS in 1954. He joined Naval Ship Research and Development Center in 1953 as a Junior Engineer and is currently the Head of the Engineering & Facilities Division Structures Department. His field of specialization is Structural Research and Development. Franklin I. Siegrist was born in Knoxville
Tenn. in 1937 receiving his earlier education in the Public Schools of Erie Pa. He attended Pennsylvania State University graduating in 1962 with a Bachelor of Science degree in Electrical Engineering having prior to that time served four years in the U. S. Navy. He was a Junior Engineer in the AC Spark Plug Division of General Motors from 1962 until 1964 at which time he came to the David Taylor Model Basin as an Electrical Engineer in the Industrial Department. He is currently Supervisory Engineer for Electrical and Electronics Engineering Structures Department Naval Ship Research and Development Center. His field of specialization is Electrical Engineering Control Systems Data Collection Systems Computer Applications to Structural Research and Hydraulic System Design. In the last of these he holds Patent Rights on a “Hydraulic Supercharge and Cooling Circuit” granted in 1970.
Two-dimensional magnetic recording (TDMR) is a novel recording architecture intended to support densities beyond those of conventional recording systems. The gains from TDMR come primarily from more powerful coding an...
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Low-resource languages are challenging to process intelligent decision systems due to limited data and resources. As an effective way of processing low-resource languages in intelligent decision systems, fuzzy linguis...
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Low-resource languages are challenging to process intelligent decision systems due to limited data and resources. As an effective way of processing low-resource languages in intelligent decision systems, fuzzy linguistic approaches excel in transforming original uncertain linguistic information into highly structured data and learning valid decision rules between complex data structures. However, existing fuzzy linguistic methods may not fully capture realistic features of multi-attribute group decision-making (MAGDM), such as incomplete and hesitant linguistic expressions, stable information fusion, and bounded rationality of decision-makers (DMs). Therefore, it is necessary to develop a collaborative fuzzy language learning system based on bounded rationality, low-resource and robust decision-making. Specifically, we present a new multi-granularity (MG) group decision-making (GDM) scheme by using MULTIMOORA (Multi-Objective Optimization by Ratio Analysis plus the full MULTIplicative form) and PT (Prospect Theory) for incomplete hesitant fuzzy linguistic information systems (I-HFL-ISs), where MG GDM aims to discover knowledge from complex MAGDM problems with MG features. To achieve the above goal, we first introduce the concept of MG-I-HFL-ISs to represent incomplete, hesitant and imprecise linguistic evaluation information offered by multiple decision-makers (DMs). Then, we apply a valid transformation scheme to convert MG-I-HFL-ISs into MG-HFL-ISs, and use the MG probability rough set (PRS) to develop a series of MG-HFL-PRSs with the support of MULTIMOORA. Afterwards, an HFL MG GDM method is designed by integrating MULTIMOORA and PT for solving MAGDM problems with MG-I-HFL-ISs. The proposed method can effectively synthesize low-resource languages and mine useful decision-making knowledge. At last, a drug selection case and a simulated case are performed for showing the rationality of the designed HFL MG GDM scheme.
In this paper, we model the effects of the physical properties of the capping layer, such as spin diffusion length (lsfcap), resistivity (ρcap), and interfacial conductance (G↑cap, G↓cap) on the spin transport acro...
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The 2nd International Workshop on Statistical Methods in Video processing, SMVP 2004, was held in Prague, Czech Republic, as an associated workshop of ECCV 2004, the 8th European Conference on computer Vision. A total...
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ISBN:
(数字)9783540302124
ISBN:
(纸本)9783540239895
The 2nd International Workshop on Statistical Methods in Video processing, SMVP 2004, was held in Prague, Czech Republic, as an associated workshop of ECCV 2004, the 8th European Conference on computer Vision. A total of 30 papers were submitted to the workshop. Of these, 17 papers were accepted for presentation and included in these proceedings, following a double-blind review process. The workshop had 42 registered participants. The focus of the meeting was on recent progress in the application of - vanced statistical methods to solve computer vision tasks. The one-day scienti?c program covered areas of high interest in vision research, such as dense rec- struction of 3D scenes, multibody motion segmentation, 3D shape inference, errors-in-variables estimation, probabilistic tracking, information fusion, optical ?owcomputation,learningfornonstationaryvideodata,noveltydetectionin- namic backgrounds, background modeling, grouping using feature uncertainty, and crowd segmentation from video. We wish to thank the authors of all submitted papers for their interest in the *** external reviewers for their commitment of time and e?ort in providing valuable recommendations for each submission. We are thankful to Vaclav Hlavac, the General Chair of ECCV 2004, and to Radim Sara, for the local organization of the workshop and registration management. We hope you will ?nd these proceedings both inspiring and of high scienti?c quality.
L10 phase FePt thin films deposited on amorphous Corning glasses and single crystal MgO (100) substrates were investigated. Epitaxial growth of the FePt (001) films was observed on MgO substrate at a deposition temper...
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The magnetization dynamics in a magnetic memory device has been analyzed self-consistently which takes into consideration the effects of the spin transfer torque. The coupled dynamics of the magnetic moment M and elec...
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