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Introduction to Data Science
This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.
Artificial Intelligence Research and Development
Artificial intelligence is no longer solely the preserve of computer scientists and researchers; it is now a part of all our lives, and hardly a day goes by without discussion and debate about the implications of its many applications in the mainstream media. This book presents the proceedings of CCIA 2023, the 25th International Conference of the Catalan Association for Artificial Intelligence, held from 25 - 27 October 2023 in Barcelona, Spain. CCIA serves as an annual forum welcoming participants from around the globe. The theme of the 2023 conference was Supportive AI, the main goals of which are to strengthen collaboration between research and industry by sharing the latest advances in ...
Multimodal Interaction in Image and Video Applications
Traditional Pattern Recognition (PR) and Computer Vision (CV) technologies have mainly focused on full automation, even though full automation often proves elusive or unnatural in many applications, where the technology is expected to assist rather than replace the human agents. However, not all the problems can be automatically solved being the human interaction the only way to tackle those applications. Recently, multimodal human interaction has become an important field of increasing interest in the research community. Advanced man-machine interfaces with high cognitive capabilities are a hot research topic that aims at solving challenging problems in image and video applications. Actuall...
Mixture Density Networks for Distribution and Uncertainty Estimation
The deep learning techniques have made neural networks the leading option for solving some computational problems and it has been shown the production of the state-of-the-art results in many fields like computer vision, automatic speech recognition, natural language processing, and audio recognition. In fact, we may be tempted to make use of neural networks directly, as we know them nowadays, in order to make predictions and solve many problems, but if the decision that has to be taken is of high risk. For instance, we could have a problem regarding the control of a nuclear power plant or the prediction of the shares evolution in the market; in this case, it would be important to look for me...
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
This book constitutes the refereed post-conference proceedings of the 21st Iberoamerican Congress on Pattern Recognition, CIARP 2016, held in Lima, Peru, in November 2016. The 69 papers presented were carefully reviewed and selected from 131 submissions. The papers feature research results in the areas of pattern recognition, biometrics, image processing, computer vision, speech recognition, and remote sensing. They constitute theoretical as well as applied contributions in many fields related to the main topics of the conference.
Convolutional Neural Networks for Style Classification
In recent years convolutional neural networks have enjoyed great success. Especially in the field of object recognition great leaps forward have been made. Researchers were able to exploit the object detection features from such networks for many useful and interesting applications like sentiment analysis and information retrieval. Unfortunately, many times the importance of style is not being considered adequately in these systems. This is partly because style is a concept that is difficult to define and labeled data is scarce. Recent developments in texture synthesis and style transfer, however, sparked new interest in the field. In particular feature correlations from convolutional neural networks, which were trained on object recognition, have been shown to work well on these tasks. I propose that such techniques can help in classifying style. In the course of this thesis I setup a experiment to show that this is indeed the case. Furthermore, I show that the performance of the CNN and the depth of the layer from which the feature correlations are taken from influences the classification performance.
Artificial Intelligence Research and Development
Artificial intelligence has become an integral part of all our lives. Development is rapid in this exciting and far-reaching field, and keeping up to date with the latest research and innovation is crucial to all those working with the technology. This book presents the proceedings of the 24th edition of CCIA, the International Conference of the Catalan Association for Artificial Intelligence, held in Sitges, Spain, from 19 – 21 October 2022. This annual event serves as a meeting point not only for researchers in AI from the Catalan speaking territories (southern France, Catalonia, Valencia, the Balearic Islands and Alghero in Italy) but for researchers from around the world. The programme...
Convolutional Neural Networks for Medical Image Processing Applications
The rise in living standards increases the expectation of people in almost every field. At the forefront is health. Over the past few centuries, there have been major developments in healthcare. Medical device technology and developments in artificial intelligence (AI) are among the most important ones. The improving technology and our ability to harness the technology effectively by means such as AI have led to unprecedented advances, resulting in early diagnosis of diseases. AI algorithms enable the fast and early evaluation of images from medical devices to maximize the benefits. While developments in the field of AI were quickly adapted to the field of health, in some cases this contribu...
