-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathreferences.bib
More file actions
193 lines (175 loc) · 9.43 KB
/
references.bib
File metadata and controls
193 lines (175 loc) · 9.43 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
%% This BibTeX bibliography file was created using BibDesk.
%% http://bibdesk.sourceforge.net/
%% Created for janetyc at 2015-03-04 17:26:45 +0800
%% Saved with string encoding Unicode (UTF-8)
@inproceedings{Lampert2009,
Abstract = {We study the problem of object classification when training and test classes are disjoint, i.e. no training examples of the target classes are available. This setup has hardly been studied in computer vision research, but it is the rule rather than the exception, because the world contains tens of thousands of different object classes and for only a very few of them image, collections have been formed and annotated with suitable class labels. In this paper, we tackle the problem by introducing attribute-based classification. It performs object detection based on a human-specified high-level description of the target objects instead of training images. The description consists of arbitrary semantic attributes, like shape, color or even geographic information. Because such properties transcend the specific learning task at hand, they can be pre-learned, e.g. from image datasets unrelated to the current task. Afterwards, new classes can be detected based on their attribute representation, without the need for a new training phase. In order to evaluate our method and to facilitate research in this area, we have assembled a new large-scale dataset, ldquoAnimals with Attributesrdquo, of over 30,000 animal images that match the 50 classes in Osherson's classic table of how strongly humans associate 85 semantic attributes with animal classes. Our experiments show that by using an attribute layer it is indeed possible to build a learning object detection system that does not require any training images of the target classes.},
Address = {Piscataway, NJ, USA},
Author = {Lampert, Christoph H. and Nickisch, Hannes and Harmeling, Stefan},
Booktitle = {Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)},
Date-Added = {2015-03-04 09:26:28 +0000},
Date-Modified = {2015-03-04 09:26:28 +0000},
Doi = {10.1109/CVPRW.2009.5206594},
Event_Name = {IEEE Computer Society Conference on Computer Vision and Pattern Recognition},
Event_Place = {Miami Beach, FL, USA},
Journal = {Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009)},
Language = {en},
Month = jun,
Organization = {Max-Planck-Gesellschaft},
Pages = {951-958},
Publisher = {IEEE Service Center},
Title = {Learning To Detect Unseen Object Classes by Between-Class Attribute Transfer},
Url = {http://www.is.tuebingen.mpg.de/fileadmin/user_upload/files/publications/CVPR2009-Lampert_[0].pdf},
Url2 = {http://www.cvpr2009.org/},
Web_Url = {http://www.cvpr2009.org/},
Year = {2009},
Bdsk-Url-1 = {http://www.is.tuebingen.mpg.de/fileadmin/user_upload/files/publications/CVPR2009-Lampert_%5B0%5D.pdf},
Bdsk-Url-2 = {http://dx.doi.org/10.1109/CVPRW.2009.5206594}}
@inproceedings{Hwang2011,
Author = {Hwang, Sung Ju and Sha, Fei and Grauman, Kristen},
Booktitle = {Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)},
Date-Added = {2015-03-04 09:22:50 +0000},
Date-Modified = {2015-03-04 09:22:50 +0000},
Pages = {1761-1768},
Publisher = {IEEE},
Title = {Sharing features between objects and their attributes.},
Year = 2011,
Bdsk-Url-1 = {http://dblp.uni-trier.de/db/conf/cvpr/cvpr2011.html#HwangSG11}}
@inproceedings{Farhadi09,
Author = {Farhadi, Ali and Endres, Ian and Hoiem, Derek and Forsyth, David},
Booktitle = {Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR},
Date-Added = {2015-02-26 12:04:41 +0000},
Date-Modified = {2015-02-26 12:04:41 +0000},
Title = {Describing objects by their attributes},
Year = {2009}}
@inproceedings{Kulesza2014,
Acmid = {2557238},
Address = {New York, NY, USA},
Author = {Kulesza, Todd and Amershi, Saleema and Caruana, Rich and Fisher, Danyel and Charles, Denis},
Booktitle = {Proceedings of the 32nd Annual ACM Conference on Human Factors in Computing Systems},
Date-Added = {2015-02-26 12:02:35 +0000},
Date-Modified = {2015-02-26 12:02:35 +0000},
Doi = {10.1145/2556288.2557238},
Isbn = {978-1-4503-2473-1},
Keywords = {concept evolution, interactive machine learning},
Location = {Toronto, Ontario, Canada},
Numpages = {10},
Pages = {3075--3084},
Publisher = {ACM},
Series = {CHI '14},
Title = {Structured Labeling for Facilitating Concept Evolution in Machine Learning},
Url = {http://doi.acm.org/10.1145/2556288.2557238},
Year = {2014},
Bdsk-Url-1 = {http://doi.acm.org/10.1145/2556288.2557238},
Bdsk-Url-2 = {http://dx.doi.org/10.1145/2556288.2557238}}
@inproceedings{Russell:INTERCHI93,
Address = {New York, NY, USA},
Author = {Russell, Daniel M. and Stefik, Mark J. and Pirolli, Peter and Card, Stuart K.},
Booktitle = {Proceedings of the INTERCHI '93 Conference on Human Factors in Computing Systems},
Date-Added = {2015-02-13 04:40:51 +0000},
Date-Modified = {2015-02-13 04:47:24 +0000},
Doi = {10.1145/169059.169209},
Location = {Amsterdam, The Netherlands},
Month = {April},
Pages = {269--276},
Publisher = {ACM},
Series = {{INTERCHI '93}},
Title = {The Cost Structure of Sensemaking},
Url = {http://doi.acm.org/10.1145/169059.169209},
Year = {1993},
Bdsk-Url-1 = {http://doi.acm.org/10.1145/169059.169209},
Bdsk-Url-2 = {http://dx.doi.org/10.1145/169059.169209}}
@inproceedings{Steidl:ICASSP05,
Author = {Steidl, Stefan and Levit, Michael and Batliner, Anton and N\"{o}th, Elmar and Niemann, Heinrich},
Booktitle = {Proceedings of the 30th IEEE International Conference on Acoustics, Speech, and Signal Processing.},
Date-Added = {2015-02-13 07:08:14 +0000},
Date-Modified = {2015-02-13 07:17:07 +0000},
Doi = {10.1109/ICASSP.2005.1415114},
Location = {Philadelphia PA, USA},
Month = {March},
Pages = {317--320},
Publisher = {IEEE Press},
Series = {{ICASSP '05}},
Title = {``Of All Things the Measure Is Man'' : Automatic Classification of Emotions and Inter-Labeler Consistency},
Volume = {1},
Year = {2005},
Bdsk-Url-1 = {http://dx.doi.org/10.1109/ICASSP.2005.1415114}}
@phdthesis{Patel:PhDThesis12,
Author = {Patel, Kayur Dushyant},
Date-Added = {2015-02-13 07:54:36 +0000},
Date-Modified = {2015-02-13 07:56:44 +0000},
School = {University of Washington},
Title = {Lowering the Barrier to Applying Machine Learning},
Url = {https://digital.lib.washington.edu/researchworks/handle/1773/22015},
Year = {2012},
Bdsk-Url-1 = {https://digital.lib.washington.edu/researchworks/handle/1773/22015}}
@techreport{Tsymbal:Techreport04,
Author = {Tsymbal, Alexey},
Date-Added = {2015-02-13 08:05:35 +0000},
Date-Modified = {2015-02-13 08:08:47 +0000},
Institution = {Department of Computer Science},
Number = {TCD-CS-2004-15},
Title = {The problem of concept drift: Definitions and related work},
Year = {2004}}
@inproceedings{Brodley:AAAI96,
Author = {Brodley, Carla E. and Friedl, Mark A.},
Booktitle = {Proceedings of the 13th National Conference on Artificial Intelligence},
Date-Added = {2015-02-13 09:30:32 +0000},
Date-Modified = {2015-02-13 09:35:21 +0000},
Location = {Portland, Oregon USA},
Month = {August},
Pages = {799--805},
Publisher = {AAAI Press},
Series = {{AAAI'96}},
Title = {Identifying and Eliminating Mislabeled Training Instances},
Url = {http://dl.acm.org/citation.cfm?id=1892875.1892994},
Year = {1996},
Bdsk-Url-1 = {http://dl.acm.org/citation.cfm?id=1892875.1892994}}
@inproceedings{Chau:CHI11,
Address = {New York, NY, USA},
Author = {Chau, Duen Horng and Kittur, Aniket and Hong, Jason I. and Faloutsos, Christos},
Booktitle = {Proceedings of the SIGCHI Conference on Human Factors in Computing Systems},
Date-Added = {2015-02-23 04:18:15 +0000},
Date-Modified = {2015-02-23 04:21:33 +0000},
Doi = {10.1145/1978942.1978967},
Location = {Vancouver, BC, Canada},
Month = {May},
Organization = {ACM},
Pages = {167--176},
Publisher = {ACM},
Series = {{CHI '11}},
Title = {Apolo: Making Sense of Large Network Data by Combining Rich User Interaction and Machine Learning},
Url = {http://doi.acm.org/10.1145/1978942.1978967},
Year = {2011},
Bdsk-Url-1 = {http://doi.acm.org/10.1145/1978942.1978967},
Bdsk-Url-2 = {http://dx.doi.org/10.1145/1978942.1978967}}
@inproceedings{Xiao:SA12,
Address = {New York, NY, USA},
Author = {Xiao, Jianxiong and Russell, Bryan C. and Hays, James and Ehinger, Krista A. and Oliva, Aude and Torralba, Antonio},
Booktitle = {Proceedings of the SIGGRAPH Asia 2012 Technical Briefs},
Date-Added = {2015-02-23 04:24:40 +0000},
Date-Modified = {2015-02-23 04:29:16 +0000},
Doi = {10.1145/2407746.2407782},
Location = {Singapore, Singapore},
Month = {November},
Pages = {36:1--36:4},
Publisher = {ACM},
Series = {{SA '12}},
Title = {Basic Level Scene Understanding: From Labels to Structure and Beyond},
Url = {http://doi.acm.org/10.1145/2407746.2407782},
Year = {2012},
Bdsk-Url-1 = {http://doi.acm.org/10.1145/2407746.2407782},
Bdsk-Url-2 = {http://dx.doi.org/10.1145/2407746.2407782}}
@article{Amershi:AI14,
Author = {Amershi, Saleema and Cakmak, Maya and Knox, W. Bradley and Kulesza, Todd},
Date-Added = {2015-02-26 06:15:24 +0000},
Date-Modified = {2015-02-26 06:24:52 +0000},
Doi = {http://dx.doi.org/10.1609/aimag.v35i4.2513},
Journal = {AI Magazine},
Month = {December},
Number = {4},
Pages = {105--102},
Title = {Power to the People: The Role of Humans in Interactive Machine Learning},
Volume = {35},
Year = {2014},
Bdsk-Url-1 = {http://dx.doi.org/10.1609/aimag.v35i4.2513}}