Извлечение предпочтений пользователя на основе методов автоматического порождения текстовых описаний изображений фотоальбома
The development of an Internet of things concept has led to an essential increase in the amount of data processed via the Internet. Multimedia data constitute a significant proportion of this information. This type of data often contains user’s personal information or copyright protected data. The issue of copyright protection of digital imagery has remained topical for the last decades. Traditional information protection tools cannot provide the required level of image protection from possible threats due to specific features of format representation. This article contains a comparative analysis of published research papers concerned with the robust image hashing as one of possible methods of copyright protection of digital imagery. It also includes a classification of robust image hashing methods, discussing their advantages and drawbacks, and their major characteristics. At the end of the article some directions of further research are outlined.
In this paper we focus on the problem of user interests’ classification in visual product recommender systems. We propose the two-stage procedure. At first, the visual features are learned by fine-tuning the convolutional neural network, e.g., MobileNet. At the second stage, we use such learnable pooling techniques as neural aggregation network and context gating in order to compute a weighted average of image features. As a result we can capture the relationships between the products images purchased by the same user. We provide an experimental study with the Amazon product dataset. It was shown that our approach achieves a F1-score of 0.90 for 15 recommendations, which is much higher when compared to 0.66 F1-measure classification of traditional averaging of the feature vector.
In this paper we focus on the problem of multi-label image recognition for visually-aware recommender systems. We propose a two stage approach in which a deep convolutional neural network is firstly fine-tuned on a part of the training set. Secondly, an attention-based aggregation network is trained to compute the weighted average of visual features in an input image set. Our approach is implemented as a mobile fashion recommender system application. It is experimentally show on the Amazon Fashion dataset that our approach achieves an F1-measure of 0.58 for 15 recommendations, which is twice as good as the 0.25 F1-measure for conventional averaging of feature vectors.
This 2-volume set constitutes the refereed proceedings of the 9th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2019, held in Madrid, Spain, in July 2019.
The 99 papers in these volumes were carefully reviewed and selected from 137 submissions. They are organized in topical sections named:
Part I: best ranked papers; machine learning; pattern recognition; image processing and representation.
Part II: biometrics; handwriting and document analysis; other applications.
This book constitutes the proceedings of the Workshops held at the International Conference on Social Informatics, SocInfo 2014, which took place in Barcelona, Spain, in November 2014. This year SocInfo 2014 included nine satellite workshops: the City Labs Workshop, the Workshop on Criminal Network Analysis and Mining, CRIMENET, the Workshop on Interaction and Exchange in Social Media, DYAD, the Workshop on Exploration of Games and Gamers, EGG, the Workshop on HistoInformatics, the Workshop on Socio-Economic Dynamics, Networks and Agent-based Models, SEDNAM, the Workshop on Social Influence, SI, the Workshop on Social Scientists Working with Start-Ups and the Workshop on Social Media in Crowdsourcing and Human Computation, SoHuman.
Darkness is the inverse state of the brightness, is obtained as an absence of noticeable light and illumination. Generally, face detection applications cannot detect any human face in a dark image, where the image has captured from the dark environment or dark night. In this manuscript, we demonstrate our experiment, where we use Contrast Stretching, Histogram Equalization and Adaptive Equalization techniques for detecting any human face in any dark image. In this paper, we also illustrate our proposed algorithm, working procedure and differentiate the pixel intensity of different stage of image processing. We essentially do this research from an application perspective, where a software application detects the human face from a dark photo or a very low-contrast image and the photo has been captured from an excessive dark environment.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
The geographic information system (GIS) is based on the first and only Russian Imperial Census of 1897 and the First All-Union Census of the Soviet Union of 1926. The GIS features vector data (shapefiles) of allprovinces of the two states. For the 1897 census, there is information about linguistic, religious, and social estate groups. The part based on the 1926 census features nationality. Both shapefiles include information on gender, rural and urban population. The GIS allows for producing any necessary maps for individual studies of the period which require the administrative boundaries and demographic information.
Existing approaches suggest that IT strategy should be a reflection of business strategy. However, actually organisations do not often follow business strategy even if it is formally declared. In these conditions, IT strategy can be viewed not as a plan, but as an organisational shared view on the role of information systems. This approach generally reflects only a top-down perspective of IT strategy. So, it can be supplemented by a strategic behaviour pattern (i.e., more or less standard response to a changes that is formed as result of previous experience) to implement bottom-up approach. Two components that can help to establish effective reaction regarding new initiatives in IT are proposed here: model of IT-related decision making, and efficiency measurement metric to estimate maturity of business processes and appropriate IT. Usage of proposed tools is demonstrated in practical cases.