Class-specific Object Research Articles

Atmospheric and spectral corrections for estimating surface albedo from satellite data using 6S code

Surface albedo is one of the most important physical parameters for climate models, because it governs the exchange of radiation between the land surface and the atmosphere. Therefore, accuracy of the measurement of surface albedo directly affects the results of a climate model. Satellite remote sensing techniques provide a more accurate pixel-level estimation of surface albedo for climate models than traditional field measurements. However, atmospheric effects and band pass limits of satellite sensors are two factors that limit accurate estimation of surface albedo from satellite data. Furthermore, comparative or global studies require a physically based model that is not optimized on one specific satellite scene, test site, and object class. Atmospheric code 6S can play this important role. Therefore, this paper develops a method for making atmospheric and spectral corrections for estimating surface albedo from satellite data using 6S code. The reliability of this method was tested in Kushiro Mire, Japan using comparisons of estimated and observed albedos. The results show that the satellite-inferred albedos agree well with the field-observed albedos, with the average error found to be about 6%. For spectral-to-broadband albedo conversion (spectral correction), results show that compensated band pass limits are better than extended band pass limits; the average error was reduced from 25% to 6%. Results also indicate that a higher spectral resolution sensor is necessary to more accurately estimate surface albedo.

Object identification deficits in dementia of the Alzheimer type: combined effects of semantic and visual proximity.

Identification deficits in dementia of the Alzheimer Type (DAT) often target specific classes of objects, sparing others. Using line drawings to uncover the etiology of such category-specific deficits may be untenable because the underlying shape primitives used to differentiate one line drawing from another are unspecified, and object form is yoked to object meaning. We used computer generated stimuli with empirically specifiable properties in a paradigm that decoupled form and meaning. In Experiment 1 visually similar or distinct blobs were paired with semantically close or disparate labels, and participants attempted to learn these pairings. By having the same blobs stand for semantically close and disparate objects and looking at shape-label confusion rates for each type of set, form and meaning were independently assessed. Overall, visual similarity of shapes and semantic similarity of labels each exacerbated object confusions. For controls, the effects were small but significant. For DAT patients more substantial visual and semantic proximity effects were obtained. Experiment 2 demonstrated that even small changes in semantic proximity could effect significant changes in DAT task performance. Labeling 3 blobs with "lion," "tiger," and "leopard" significantly elevated DAT confusion rates compared to exactly the same blobs labeled with "lion," "tiger," and "zebra." In conclusion both visual similarity and semantic proximity contributed to the identification errors of DAT patients.

The Late Bronze Egyptian Garrison at Beth Shan: A Study of Levels VII and VIII

The University Museum excavated at Beth Shan from 1921-1934, when stratigraphical methods were first being developed. For this study the two Late Bronze levels (VII and VIII) have been reevaluated by the careful analysis of field records, photographs, and drawings along with the restudy of all artifacts housed in The University Museum and a selection of objects in the Rockefeller Museum in Jerusalem. The structures of these levels have parallels in New Kingdom Egypt and Late Bronze/Early Iron Age sites of southern Levant and the Sinai. Included are contributions by 13 specialists on specific classes of objects and technologies. University Museum Monograph, 85

Metals in Ancient Israel: Archaeological Interperetation of Chemical Analysis

AbstractOver a thousand metal finds are now known from Chalcolithic and Early Bronze habitation sites, burial caves, and hoards in Israel and Jordan. To answer the question as to how these artifacts were made, more than 200 objects were sampled for metallographic analysis and for chemical analysis by electron‐probe X‐ray microanalysis and by atomic absorption spectrophotometry.In the Chalcolithic period (4th millennium BC), within a confined zone of southern Israel and Jordan, three entirely different groups of metal objects were found together. Various materials (Cu‐As‐Sb; Au; Cu) from totally separate sources were used in diverse production methods to produce specific classes of objects, of a specific shape and color, totally different from one another.In contrast, the components of Early Bronze Age (3rd millennium BC) metal production indicate a fundamental change in the structure and level of craft specialization. This change may be recognized mainly by the unity of the repertory of objects and the use of the same source‐metal (Ag; Au; Cu) for a wider range of products, as well as by the total technological and geographical separation between extraction and production.The transformation from proto‐urban to urban society documents an important stage of social, economic, and political development in Early Bronze Age Israel and Jordan. Many explanations have been offered for this transformation, most of them based on external intervention or stimulus. This paper adds to the existing arguments for the beginning of urbanization, the missing local socioeconomic factor, based on changes in social complexity as reflected in the first two thousand years of metallurgy.

Object recognition by a massively parallel 2-D neural architecture

The use of a massively parallel neural array for multiple 2-D object recognition is explored. The array architecture has a parallel modular form with each module being trained over a specific object class. One test bed is developed using alphabetic characters which have been subjected to a scale factor and rotational operations. This test bed provides a simultaneous measure of geometric invariance and of character recognition. The performance of the modular design is benchmarked against a backprop-trained multilayer perceptron network of equivalent generality. A second test of the modular array is conducted using TV and FLIR images. This second evaluation assesses the ability to extract obejct signatures from a clutter background.

LEARNING BLACKBOARD-BASED SCHEDULING ALGORITHMS FOR COMPUTER VISION

The goal of image understanding by computer is to identify objects in visual images and (if necessary) to determine their location and orientation. Objects are identified by comparing data extracted from images to an a priori description of the object or object class in memory. It is a generally accepted premise that, in many domains, the timely and appropriate use of knowledge can substantially reduce the complexity of matching image data to object descriptions. Because of the variety and scope of knowledge relevant to different object classes, contexts and viewing conditions, blackboard architectures are well suited to the task of selecting and applying the relevant knowledge to each situation as it is encountered. This paper reviews ten years of work on the UMass VISIONS system and its blackboard-based high-level component, the schema system. The schema system could interpret complex natural scenes when given carefully crafted knowledge bases describing the domain, but its application in practice was limited by the problem of model (knowledge base) acquisition. Experience with the schema system convinced us that learning techniques must be embedded in vision systems of the future to reduce or eliminate the knowledge engineering aspects of system construction. The Schema Learning System (SLS) is a supervised learning system for acquiring knowledge-directed object recognition (control) strategies from training images. The recognition strategies are precompiled reactive sequences of knowledge source invocations that replace the dynamic scheduler found in most blackboard systems. Each strategy is specialized to recognize instances of a specific object class within a specific context. Since the strategies are learned automatically, the knowledge base contains only general-purpose knowledge sources rather than problem-specific control heuristics or sequencing information.

Methods for constructing a management information base (mib) in transmission network operations

AbstractMethods of realizing a management information base (MIB) under a CMIS/CMIP environment using RDBMs for realizing a transmissions network operations system using the OSI management techniques are presented. A method of constructing an MIB by an attribute unit table with respect to the restrictions of CMIP without a specific object class in the operations process is proposed. Corresponding to management information that has become complicated with the times, this method proposes a mechanism of global searching independent of management object definitions by deriving a general procedure required for attribute operations within an agent system to make the CMIS processing codes as independent management object definitions and storing the forementioned procedure in an MIB. In addition, this construction method was evaluated by using an MIB constructed experimentally and the realizability of the proposed method of construction of MIBs and the performance of the experimental MIB evaluated by the experiment are presented. This MIB construction method is applicable to high‐level agent systems that are complicated and of large scale.

An automated search for widely spaced gravitational lenses performed on 25 grens plates

view Abstract Citations (2) References (24) Co-Reads Similar Papers Volume Content Graphics Metrics Export Citation NASA/ADS AN Automated Search for Widely Spaced Gravitational Lenses Performed on 25 Grens Plates Beauchemin, M. ; Borra, E. F. Abstract An automated search for gravitational lenses has been conducted on 25 grens plates taken from the automated CFHT-Laval survey. We surveyed a total of 39966 objects on 15.7 sq deg to B~21. The plates have excellent image quality with FWHM ~ 1". All close pairs (1.5" < separation < 10"), irrespective of image extendedness, having similar colors and possessing characteristics of quasars have been extracted from our existing databases. Between 600 and 1200 bona fide quasars should have been examined. Positions, magnitudes, and spectra] characteristics of the 11 lens candidates found are furnished. A noteworthy aspect of the Laval survey is the capacity to quantify the selection effects in finding specific classes of objects; we give, therefore, the basic information necessary for modeling the selection effects of our survey. We estimate that ~15% of the primaries are quasars, yielding to a probable value of 0.02%-0.04% lensed quasars with separations between 1.5"-10", consistent with the recent predictions of Fukugita & Turner [MNRAS, in press (1991)]. Publication: The Astronomical Journal Pub Date: February 1992 DOI: 10.1086/116069 Bibcode: 1992AJ....103..405B Keywords: Astronomical Photography; Gravitational Lenses; Sky Surveys (Astronomy); Quasars; Red Shift; Spatial Distribution; Visible Spectrum; Astrophysics; GRAVITATIONAL LENSING full text sources ADS | data products SIMBAD (32) NED (32)