### Table 7: Indexing PDF files

2006

"... In PAGE 14: ... However, does it contain the same amount of information that Tracker and Beagle? Section 7 of this document tries to get answers for this question. Again CPU usage is the smallest for JIndex ( Table7 ) and allows one to perform other tasks on the system at the same time. Tracker (88,06%+10,51%=98,57%) does not allow anything except indexing.... ..."

### TABLE1 DOCUMENTS IDENTIFICATION METHODS EVALUATION RESULTS Slideshow

### Table 5. Performance comparison of the networks for script identification of document images.

2002

Cited by 2

### Table 2: Road Intersection Identification Evaluation

2004

"... In PAGE 6: ... If we exclude the intersections detected on highways where the road widths vary and difficult to predict, we achieved 83% precision and 65% recall with NAVTEQ data. In order to explain our experiments, we show the performance of a sub-area (with 106 intersections) of the larger tested area in Table2 . As shown in Table 2(a), there are originally more than 30 intersection points on the NAVTEQ vector that match with the corresponding intersections on images, while there are only about four of these intersections on the TIGER/Lines.... In PAGE 6: ... In order to explain our experiments, we show the performance of a sub-area (with 106 intersections) of the larger tested area in Table 2. As shown in Table2 (a), there are originally more than 30 intersection points on the NAVTEQ vector that match with the corresponding intersections on images, while there are only about four of these intersections on the TIGER/Lines. This is because the NAVTEQ vector data has a very high accuracy.... In PAGE 6: ... VMF [10] is an example of such filter. As shown in Table2 , the VMF filter improves the precision, although it reduces the recall. The VMF filter works based on the fact that there is a significant amount of regularity in terms of the relative positions of the intersections on the vector and the detected (corresponding) intersections on the imagery across data sets.... ..."

Cited by 5

### Table 7-4. Mathematical Formula Expressions Needed to Solve Design Problems.

"... In PAGE 72: ...). Table7 -1. Data Collection Design Determination.... In PAGE 72: ...ype of non-statistical design is appropriate (e.g., haphazard or judgmental). If the design is non-statistical, fill in the following table and skip to worksheet activity 5; if the design is statistical, proceed to the next table in this worksheet activity. Table7 -2. Data Collection Design Alternatives.... In PAGE 73: ...Rev. 1 A-37 Table7 -3. Statistical Design Determination.... In PAGE 73: ... For example, if a mean concentration of a COPC will be measured by a field screening instrument rather than through laboratory analyses, the model that relates the field screening results to the concentration results must be specified, along with any assumptions upon which the model is based. Table7 -5. Relationships and Assumptions Between True and Measured Values.... In PAGE 74: ... Vary the Type I and Type II error rates (and other inputs in the equations) to examine the relationship between the number of samples and the inputs. Table7 -6. Calculation of Number of Samples for Each Design Alternative.... In PAGE 74: ...e.g., spatial and temporal boundaries or scope of the project). Table7 -7. Results of Trade-Off Analysis.... In PAGE 75: ... The results of the trade-off analyses should lead to one of two outcomes: (a) either the selection of a design that most efficiently meets all of the DQO constraints, or (b) the modification of one or more outputs from DQO process Steps 1 through 6 and the selection of a design that meets the new constraints. Table7 -8. Selection of Appropriate Data Collection Design.... In PAGE 75: ... The most efficient way to deal with uncertainties about the conceptual site model, historical data, or unforeseen implementation problems is to plan an alternative course of action that may be appropriate. Table7 -9. Outline of Alternative Strategies.... In PAGE 76: ...Rev. 1 A-40 Table7 -10. Key Features of Selected Design.... In PAGE 76: ...istribution of the parameter of interest (e.g., the mean concentration is assumed Gaussian) y Statistical independence y Distribution of the population of interest y Model that shows the relationship between the variable being measured and the variable of interest. Table7 -11. Documentation on Theoretical Assumptions.... ..."

### Table 1: Mathematical Formulae for Signal Classes

"... In PAGE 3: ... Figure 1 displays the original nonrandomized ver- sions in the top row of subplots, and one instance each of the randomized versions in the bottom row of subplots. Table1 lists the mathematical formu- lae for the test signal classes. These formulae are valid for both the randomized and original non- randomized versions with the appropriate choice of parameters.... ..."

### Table 1. Taxonomy of techniques for PDF document analysis

2006

Cited by 2

### Table 1: Mathematical Formulae for Signal Classes

1999

"... In PAGE 2: ... Figure 1 displays the original nonrandomized ver- sions in the top row of subplots, and one instance each of the randomized versions in the bottom row of subplots. Table1 lists the mathematical formulae for the test signal classes. These formu- lae are valid for both the randomized and orig- inal nonrandomized versions with the appropri- ate choice of parameters.... ..."

Cited by 1

### Table 1: Test document images. The thirdcolumn gives the number of documents per category, the fourth

"... In PAGE 15: ...3 Evaluation of JB2 and IW44 on Complex Document Images Assuming a satisfactory foreground/background/mask separation, we can focus on the separate compres- sion of the three sub-images. Our test sample, as described in Table1 , is composed of 70 document images (grouped in 12 categories) that would be problematic to transfer to a \symbolic quot; form (for instance PDF). They contain highly textured background (Cuisine, WashPost, Maps, Usa), handwriting (Brattain, Usa), a mixture of text and images (Forbes, Hobbylobby, Maps), mathematical symbols (Flammarion), hand drawings (Curry, Microphone.... ..."

### Table 3-2). The calculations for each case are summarized below; detailed documentation of the mathematical

in DISCLAIMER

2003

"... In PAGE 6: ........................................ 2-8 Table3 -1. Contents of the PRODUCT CATEGORY File .... In PAGE 6: ..................................... 3-4 Table3 -2. Contents of the PRODUCT-FORMULATION File .... In PAGE 27: ... Table3 -1. Contents of the PRODUCT CATEGORY File FIELD NAME FIELD TYPE UNITS FIELD DESCRIPTION Product, Product Class, or Industry ID Character -- 4-digit SIC industry code or 5-digit SIC product class code or 7-digit SIC product code to which has been added an additional 2 digits to enable additional product classification.... In PAGE 27: ...and a unique identification code (i.e., the Formulation ID) that identifies the data source and the location of the data within the source document. Table3 -2 presents information on the principal data elements in the PRODUCT-FORMULATION file. Appendix B contains all 12,595 records in the... In PAGE 28: ... Table3 -2. Contents of the PRODUCT-FORMULATION File FIELD NAME FIELD TYPE UNITS FIELD DESCRIPTION Product ID Character -- SIC product code 1 .... In PAGE 93: ... The program selects the first category in the scheme and the first product ID associated with that category. Next, from the PRODUCT-FORMULATION file (see Table3 -2), the program selects the first formulation associated with the product ID and notes the environments to which the formulation applies. The program then accesses the PRODUCT-CHEMICAL file (see Table 4-1) to identify all chemicals (CAS numbers) associated with the product ID and formulation.... ..."