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	Author	V. Kober; Mikhail Mozerov; J. Alvarez-Borrego; I.A. Ovseyevich
	Title	Adaptive Correlation Filters for Pattern Recognition			Type	Journal
	Year	2006	Publication	Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	16	Issue	3	Pages	425-431
	Keywords	Pattern recognition, Correlation filters, A adaptive filters
	Abstract	Adaptive correlation filters based on synthetic discriminant functions (SDFs) for reliable pattern recognition are proposed. A given value of discrimination capability can be achieved by adapting a SDF filter to the input scene. This can be done by iterative training. Computer simulation results obtained with the proposed filters are compared with those of various correlation filters in terms of recognition performance.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	ISE			Approved	no
	Call Number	ISE @ ise @ KMA2006a			Serial	673
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	Author	V. Kober; Mikhail Mozerov; J. Alvarez-Borrego; I.A. Ovseyevich
	Title	Pattern Recognition of Fragmented Objects with Adaptive Correlation Filters			Type	Miscellaneous
	Year	2006	Publication	Topical Meeting on Optoinformatics / Information Photonics, 150–151	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Saint-Petersburg (Russia)
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	ISE			Approved	no
	Call Number	ISE @ ise @ KMA2006b			Serial	674
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	Author	V. Chapaprieta; Ernest Valveny
	Title	Handwritten Digit Recognition Using Point Distribution Models.			Type	Miscellaneous
	Year	2001	Publication	Proceedings of the IX Spanish Symposium on Pattern Recognition and Image Analysis, 1:49–54.	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ ChV2001			Serial	83
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	Author	V. Chapaprieta
	Title	Reconocimiento de caracteres manuscritos mediante modelos de distribucion de puntos (PDM)			Type	Report
	Year	2000	Publication	CVC Technical Report #41	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	CVC (UAB)
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	Admin @ si @ Cha2000			Serial	342
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	Author	Utkarsh Porwal; Alicia Fornes; Faisal Shafait (eds)
	Title	Frontiers in Handwriting Recognition. International Conference on Frontiers in Handwriting Recognition. 18th International Conference, ICFHR 2022			Type	Book Whole
	Year	2022	Publication	Frontiers in Handwriting Recognition.	Abbreviated Journal
	Volume	13639	Issue		Pages
	Keywords
	Abstract
	Address	ICFHR 2022, Hyderabad, India, December 4–7, 2022
	Corporate Author				Thesis
	Publisher	Springer	Place of Publication		Editor	Utkarsh Porwal; Alicia Fornes; Faisal Shafait
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-031-21648-0	Medium
	Area		Expedition		Conference	ICFHR
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ PFS2022			Serial	3809
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	Author	Umut Guclu; Yagmur Gucluturk; Meysam Madadi; Sergio Escalera; Xavier Baro; Jordi Gonzalez; Rob van Lier; Marcel A. J. van Gerven
	Title	End-to-end semantic face segmentation with conditional random fields as convolutional, recurrent and adversarial networks			Type	Miscellaneous
	Year	2017	Publication	Arxiv	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	arXiv:1703.03305 Recent years have seen a sharp increase in the number of related yet distinct advances in semantic segmentation. Here, we tackle this problem by leveraging the respective strengths of these advances. That is, we formulate a conditional random field over a four-connected graph as end-to-end trainable convolutional and recurrent networks, and estimate them via an adversarial process. Importantly, our model learns not only unary potentials but also pairwise potentials, while aggregating multi-scale contexts and controlling higher-order inconsistencies. We evaluate our model on two standard benchmark datasets for semantic face segmentation, achieving state-of-the-art results on both of them.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	HuPBA; ISE; 600.098; 600.119			Approved	no
	Call Number	Admin @ si @ GGM2017			Serial	2932
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	Author	Umapada Pal; Partha Pratim Roy; N. Tripathya; Josep Llados
	Title	Multi-oriented Bangla and Devnagari text recognition			Type	Journal Article
	Year	2010	Publication	Pattern Recognition	Abbreviated Journal	PR
	Volume	43	Issue	12	Pages	4124–4136
	Keywords
	Abstract	There are printed complex documents where text lines of a single page may have different orientations or the text lines may be curved in shape. As a result, it is difficult to detect the skew of such documents and hence character segmentation and recognition of such documents are a complex task. In this paper, using background and foreground information we propose a novel scheme towards the recognition of Indian complex documents of Bangla and Devnagari script. In Bangla and Devnagari documents usually characters in a word touch and they form cavity regions. To take care of these cavity regions, background information of such documents is used. Convex hull and water reservoir principle have been applied for this purpose. Here, at first, the characters are segmented from the documents using the background information of the text. Next, individual characters are recognized using rotation invariant features obtained from the foreground part of the characters. For character segmentation, at first, writing mode of a touching component (word) is detected using water reservoir principle based features. Next, depending on writing mode and the reservoir base-region of the touching component, a set of candidate envelope points is then selected from the contour points of the component. Based on these candidate points, the touching component is finally segmented into individual characters. For recognition of multi-sized/multi-oriented characters the features are computed from different angular information obtained from the external and internal contour pixels of the characters. These angular information are computed in such a way that they do not depend on the size and rotation of the characters. Circular and convex hull rings have been used to divide a character into smaller zones to get zone-wise features for higher recognition results. We combine circular and convex hull features to improve the results and these features are fed to support vector machines (SVM) for recognition. From our experiment we obtained recognition results of 99.18% (98.86%) accuracy when tested on 7515 (7874) Devnagari (Bangla) characters.
	Address
	Corporate Author				Thesis
	Publisher	Elsevier	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ PRT2010			Serial	1337
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	Author	Trevor Canham; Javier Vazquez; Elise Mathieu; Marcelo Bertalmío
	Title	Matching visual induction effects on screens of different size			Type	Journal Article
	Year	2021	Publication	Journal of Vision	Abbreviated Journal	JOV
	Volume	21	Issue	6(10)	Pages	1-22
	Keywords
	Abstract	In the film industry, the same movie is expected to be watched on displays of vastly different sizes, from cinema screens to mobile phones. But visual induction, the perceptual phenomenon by which the appearance of a scene region is affected by its surroundings, will be different for the same image shown on two displays of different dimensions. This phenomenon presents a practical challenge for the preservation of the artistic intentions of filmmakers, because it can lead to shifts in image appearance between viewing destinations. In this work, we show that a neural field model based on the efficient representation principle is able to predict induction effects and how, by regularizing its associated energy functional, the model is still able to represent induction but is now invertible. From this finding, we propose a method to preprocess an image in a screen–size dependent way so that its perception, in terms of visual induction, may remain constant across displays of different size. The potential of the method is demonstrated through psychophysical experiments on synthetic images and qualitative examples on natural images.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	CIC			Approved	no
	Call Number	Admin @ si @ CVM2021			Serial	3595
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	Author	Trevor Canham; Javier Vazquez; D Long; Richard F. Murray; Michael S Brown
	Title	Noise Prism: A Novel Multispectral Visualization Technique			Type	Journal Article
	Year	2021	Publication	31st Color and Imaging Conference	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	A novel technique for visualizing multispectral images is proposed. Inspired by how prisms work, our method spreads spectral information over a chromatic noise pattern. This is accomplished by populating the pattern with pixels representing each measurement band at a count proportional to its measured intensity. The method is advantageous because it allows for lightweight encoding and visualization of spectral information while maintaining the color appearance of the stimulus. A four alternative forced choice (4AFC) experiment was conducted to validate the method’s information-carrying capacity in displaying metameric stimuli of varying colors and spectral basis functions. The scores ranged from 100% to 20% (less than chance given the 4AFC task), with many conditions falling somewhere in between at statistically significant intervals. Using this data, color and texture difference metrics can be evaluated and optimized to predict the legibility of the visualization technique.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	CIC
	Notes	MACO; CIC			Approved	no
	Call Number	Admin @ si @ CVL2021			Serial	4000
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	Author	Tomas Sixta; Julio C. S. Jacques Junior; Pau Buch Cardona; Eduard Vazquez; Sergio Escalera
	Title	FairFace Challenge at ECCV 2020: Analyzing Bias in Face Recognition			Type	Conference Article
	Year	2020	Publication	ECCV Workshops	Abbreviated Journal
	Volume	12540	Issue		Pages	463-481
	Keywords
	Abstract	This work summarizes the 2020 ChaLearn Looking at People Fair Face Recognition and Analysis Challenge and provides a description of the top-winning solutions and analysis of the results. The aim of the challenge was to evaluate accuracy and bias in gender and skin colour of submitted algorithms on the task of 1:1 face verification in the presence of other confounding attributes. Participants were evaluated using an in-the-wild dataset based on reannotated IJB-C, further enriched 12.5K new images and additional labels. The dataset is not balanced, which simulates a real world scenario where AI-based models supposed to present fair outcomes are trained and evaluated on imbalanced data. The challenge attracted 151 participants, who made more 1.8K submissions in total. The final phase of the challenge attracted 36 active teams out of which 10 exceeded 0.999 AUC-ROC while achieving very low scores in the proposed bias metrics. Common strategies by the participants were face pre-processing, homogenization of data distributions, the use of bias aware loss functions and ensemble models. The analysis of top-10 teams shows higher false positive rates (and lower false negative rates) for females with dark skin tone as well as the potential of eyeglasses and young age to increase the false positive rates too.
	Address	Virtual; August 2020
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ECCVW
	Notes	HUPBA			Approved	no
	Call Number	Admin @ si @ SJB2020			Serial	3499
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	Author	Thomas B. Moeslund; Sergio Escalera; Gholamreza Anbarjafari; Kamal Nasrollahi; Jun Wan
	Title	Statistical Machine Learning for Human Behaviour Analysis			Type	Journal Article
	Year	2020	Publication	Entropy	Abbreviated Journal	ENTROPY
	Volume	25	Issue	5	Pages	530
	Keywords	action recognition; emotion recognition; privacy-aware
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	HuPBA; no proj			Approved	no
	Call Number	Admin @ si @ MEA2020			Serial	3441
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	Author	Thierry Brouard; Jordi Gonzalez; Caifeng Shan; Massimo Piccardi; Larry S. Davis
	Title	Special issue on background modeling for foreground detection in real-world dynamic scenes			Type	Journal Article
	Year	2014	Publication	Machine Vision and Applications	Abbreviated Journal	MVAP
	Volume	25	Issue	5	Pages	1101-1103
	Keywords
	Abstract	Although background modeling and foreground detection are not mandatory steps for computer vision applications, they may prove useful as they separate the primal objects usually called “foreground” from the remaining part of the scene called “background”, and permits different algorithmic treatment in the video processing field such as video surveillance, optical motion capture, multimedia applications, teleconferencing and human–computer interfaces. Conventional background modeling methods exploit the temporal variation of each pixel to model the background, and the foreground detection is made using change detection. The last decade witnessed very significant publications on background modeling but recently new applications in which background is not static, such as recordings taken from mobile devices or Internet videos, need new developments to detect robustly moving objects in challenging environments. Thus, effective methods for robustness to deal both with dynamic backgrounds, i
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0932-8092	ISBN		Medium
	Area		Expedition		Conference
	Notes	ISE; 600.078			Approved	no
	Call Number	BGS2014a			Serial	2411
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	Author	Thierry Brouard; A. Delaplace; Muhammad Muzzamil Luqman; H. Cardot; Jean-Yves Ramel
	Title	Design of Evolutionary Methods Applied to the Learning of Bayesian Nerwork Structures			Type	Book Chapter
	Year	2010	Publication	Bayesian Network	Abbreviated Journal
	Volume		Issue		Pages	13-37
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher	Sciyo	Place of Publication		Editor	Ahmed Rebai
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-953-307-124-4	Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	Admin @ si @ BDL2010			Serial	1461
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	Author	Theo Gevers; Arjan Gijsenij; Joost Van de Weijer; J.M. Geusebroek
	Title	Color in Computer Vision: Fundamentals and Applications			Type	Book Whole
	Year	2012	Publication	Color in Computer Vision: Fundamentals and Applications	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher	The Wiley-IS&T Series in Imaging Science and Technology	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-0-470-89084-4	Medium
	Area		Expedition		Conference
	Notes	ALTRES;ISE			Approved	no
	Call Number	Admin @ si @ GGG2012a			Serial	2068
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	Author	Thanh Nam Le; Muhammad Muzzamil Luqman; Anjan Dutta; Pierre Heroux; Christophe Rigaud; Clement Guerin; Pasquale Foggia; Jean Christophe Burie; Jean Marc Ogier; Josep Llados; Sebastien Adam
	Title	Subgraph spotting in graph representations of comic book images			Type	Journal Article
	Year	2018	Publication	Pattern Recognition Letters	Abbreviated Journal	PRL
	Volume	112	Issue		Pages	118-124
	Keywords	Attributed graph; Region adjacency graph; Graph matching; Graph isomorphism; Subgraph isomorphism; Subgraph spotting; Graph indexing; Graph retrieval; Query by example; Dataset and comic book images
	Abstract	Graph-based representations are the most powerful data structures for extracting, representing and preserving the structural information of underlying data. Subgraph spotting is an interesting research problem, especially for studying and investigating the structural information based content-based image retrieval (CBIR) and query by example (QBE) in image databases. In this paper we address the problem of lack of freely available ground-truthed datasets for subgraph spotting and present a new dataset for subgraph spotting in graph representations of comic book images (SSGCI) with its ground-truth and evaluation protocol. Experimental results of two state-of-the-art methods of subgraph spotting are presented on the new SSGCI dataset.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG; 600.097; 600.121			Approved	no
	Call Number	Admin @ si @ LLD2018			Serial	3150
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