[Gzz-commits] manuscripts/Paper IV03.cls paper.tex

[Janne V. Kujala]

CVSROOT:        /cvsroot/gzz
Module name:    manuscripts
Changes by:     Janne V. Kujala <address@hidden>        03/04/25 04:15:31

Modified files:
        Paper          : IV03.cls paper.tex 

Log message:
        unify citation format

CVSWeb URLs:
http://savannah.gnu.org/cgi-bin/viewcvs/gzz/manuscripts/Paper/IV03.cls.diff?tr1=1.1&tr2=1.2&r1=text&r2=text
http://savannah.gnu.org/cgi-bin/viewcvs/gzz/manuscripts/Paper/paper.tex.diff?tr1=1.129&tr2=1.130&r1=text&r2=text

Patches:
Index: manuscripts/Paper/IV03.cls
diff -u manuscripts/Paper/IV03.cls:1.1 manuscripts/Paper/IV03.cls:1.2
--- manuscripts/Paper/IV03.cls:1.1      Tue Mar 18 04:23:34 2003
+++ manuscripts/Paper/IV03.cls  Fri Apr 25 04:15:31 2003
@@ -503,8 +503,10 @@
 %
 %% separate citations with "], ["
 address@hidden@address@hidden
address@hidden@address@hidden@citeb:=#2\do address@hidden@citea{],
address@hidden address@hidden@citeb}{{\bf address@hidden {Citation 
address@hidden' on
address@hidden@address@hidden@citeb:=#2\do address@hidden@citea{%
+%], [%
+, % --Jvk: don't add extra brackets
address@hidden address@hidden@citeb}{{\bf address@hidden {Citation 
address@hidden' on
 page \thepage \space undefined}}%
 {\csname address@hidden@citeb\endcsname}}}{#1}}
 
Index: manuscripts/Paper/paper.tex
diff -u manuscripts/Paper/paper.tex:1.129 manuscripts/Paper/paper.tex:1.130
--- manuscripts/Paper/paper.tex:1.129   Thu Apr 24 08:11:09 2003
+++ manuscripts/Paper/paper.tex Fri Apr 25 04:15:31 2003
@@ -67,10 +67,6 @@
 
 %FIXME: Fig 1, a): Mark the link clearer. Try to avoid line crossing.
 
-%FIXME: The citation might be better if only a unified format is used.  
-%E.g., "point (see, e.g., Heeger[16])" -> "point[16]" . (Optional)
-%XXX: is there a reason for inserting "], [" between citations?
-
 %FIXME: The fonts should be uniform in the topics of figure 1 and table 1.
 
 %FIXME: Revise the spelling and grammar errors, esp. grammar of long sentences.
@@ -276,9 +272,9 @@
 Textures have been synthesized in several ways: 
procedurally\cite{perlin-noise-intro},
 using 
 other textures as a starting point\cite{heeger95pyramid},
-perceptually, for visualizing surface 
orientation\cite{schweitzer83texturing,interrante97illustrating} and scalar or 
vector fields\cite{ware95texture},
-and statistically, as samples from a probability distribution on a random field
-\cite{cross83markov,geman84stochastic}.
+perceptually, for visualizing surface 
orientation\cite{interrante97illustrating,schweitzer83texturing} and scalar or 
vector fields\cite{ware95texture},
+and statistically, as samples from a probability distribution on a 
+random field\cite{cross83markov,geman84stochastic}.
 % FIXME: grammar
 % XXX: there's overlap between the enumerated cases
 
@@ -293,7 +289,7 @@
 
 Psychophysical studies on texture perception have mostly concentrated
 on pre-attentive 
-\emph{visual texture 
discrimination}\cite{julesz62visualpattern,bergen91theories}, 
+\emph{visual texture 
discrimination}\cite{bergen91theories,julesz62visualpattern}, 
 the ability of human observers to effortlessly discriminate
 pairs of certain textures. 
 %Discrimination models can provide insight on the pre-attentive 
@@ -304,27 +300,26 @@
 However, the textons are hard to define formally.
 
 Simpler, filtering-based models can explain texture discrimination
-equally well \cite{bergen88earlyvision}.
+equally well\cite{bergen88earlyvision}.
 In these models, a bank of linear filters is applied to the texture followed
 by a nonlinearity and then another set of filters to extract features
-(see, e.g., Heeger\cite{heeger95pyramid}).
+(see, e.g., %Heeger
+\cite{heeger95pyramid}).
 %FIXME: grammar and citation
 There is also physiological evidence of the filtering processes:
 %The first stages 
 %of visual perception 
 %are fairly well known
 in the visual cortex, there are cells sensitive to different 
-frequencies, orientations, and locations in the visual field
-%(see, e.g.,~Bruce et al
+frequencies, orientations, and locations in the visual field%(see, e.g.,~Bruce 
et al
 \cite{bruce96visualperception}.
 
 On a higher level, the correlations between local features are combined 
 by forming contours and possibly
-other higher-level constructions %(see, e.g.,
+other higher-level constructions%(see, e.g.,
 \cite{saarinen97integration}. 
 These higher levels are not yet thoroughly understood;
-some theories
-%(see, e.g., Biederman%
+some theories%(see, e.g., Biederman%
 \cite{biederman87}
 assume certain primitive shapes whose 
 structure facilitates recognition.
@@ -340,7 +335,7 @@
 (no color, lack of frequency-band interaction, etc.).
 For some natural texture sets, 
 three dimensions have also been
-sufficient \cite{rao96texturenaming}, but often semantic connections cause the
+sufficient\cite{rao96texturenaming}, but often semantic connections cause the
 similarity to be context-dependant, making it hard to assess the 
 dimensionality.
 %% XXX: this is something we should experiment with our textures
@@ -729,7 +724,7 @@
 Features that are orthogonal for human perception 
 (e.g.,~color and  direction of fastest luminance change)
 should be independently random, and features not orthogonal 
-(e.g. colors of neighbouring pixels) 
+(e.g., colors of neighbouring pixels) 
 should be correlated so as to maximize the entropy.
 %For example, pixels on a small area should correlate enough to
 %facilitate perception of contours.
@@ -1078,8 +1073,7 @@
 any mapping of the texture is fine, as long as it repeats
 with the selected repeating unit. For example, a texture can
 repeat multiple times inside the repeating unit, or can be skewed
-w.r.t.~the repeating unit. 
-%FIXME: spell out w.r.t?(Optional)
+with respect to the repeating unit. 
 Again, a heuristic distribution is used which does not skew or scale
 the basis texture too much too often.
 
@@ -1399,7 +1393,7 @@
 
 Another question is how many textures would the user have to remember
 for it to be useful.
-Studies of web cache statistics (see, e.g. \cite{breslau99web}) 
+Studies of web cache statistics (see, e.g., \cite{breslau99web}) 
 have shown that file popularity approximately follows Zipf's law
 so that a small number of documents accounts 
 for most of the use,