Multimodal Computational Attention For Scene Understanding And Robotics
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| Author | : Boris Schauerte |
| Publisher | : Springer |
| Total Pages | : 220 |
| Release | : 2016-05-11 |
| Genre | : Technology & Engineering |
| ISBN | : 3319337963 |
This book presents state-of-the-art computational attention models that have been successfully tested in diverse application areas and can build the foundation for artificial systems to efficiently explore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recent computational attention models for processing visual and acoustic input. It covers the biological background of visual and auditory attention, as well as bottom-up and top-down attentional mechanisms and discusses various applications. In the first part new approaches for bottom-up visual and acoustic saliency models are presented and applied to the task of audio-visual scene exploration of a robot. In the second part the influence of top-down cues for attention modeling is investigated.
| Author | : Michael Ying Yang |
| Publisher | : Academic Press |
| Total Pages | : 424 |
| Release | : 2019-07-16 |
| Genre | : Technology & Engineering |
| ISBN | : 0128173599 |
Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, thus helping foster interdisciplinary interaction and collaboration between these realms. Researchers collecting and analyzing multi-sensory data collections – for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites will find this book to be very useful. - Contains state-of-the-art developments on multi-modal computing - Shines a focus on algorithms and applications - Presents novel deep learning topics on multi-sensor fusion and multi-modal deep learning
| Author | : Grotz, Markus |
| Publisher | : KIT Scientific Publishing |
| Total Pages | : 202 |
| Release | : 2021-12-21 |
| Genre | : Computers |
| ISBN | : 3731511010 |
Visual perception is one of the most important sources of information for both humans and robots. A particular challenge is the acquisition and interpretation of complex unstructured scenes. This work contributes to active vision for humanoid robots. A semantic model of the scene is created, which is extended by successively changing the robot's view in order to explore interaction possibilities of the scene.
| Author | : Matei Mancas |
| Publisher | : Springer |
| Total Pages | : 456 |
| Release | : 2016-06-29 |
| Genre | : Medical |
| ISBN | : 149393435X |
This both accessible and exhaustive book will help to improve modeling of attention and to inspire innovations in industry. It introduces the study of attention and focuses on attention modeling, addressing such themes as saliency models, signal detection and different types of signals, as well as real-life applications. The book is truly multi-disciplinary, collating work from psychology, neuroscience, engineering and computer science, amongst other disciplines. What is attention? We all pay attention every single moment of our lives. Attention is how the brain selects and prioritizes information. The study of attention has become incredibly complex and divided: this timely volume assists the reader by drawing together work on the computational aspects of attention from across the disciplines. Those working in the field as engineers will benefit from this book’s introduction to the psychological and biological approaches to attention, and neuroscientists can learn about engineering work on attention. The work features practical reviews and chapters that are quick and easy to read, as well as chapters which present deeper, more complex knowledge. Everyone whose work relates to human perception, to image, audio and video processing will find something of value in this book, from students to researchers and those in industry.
| Author | : Cédric Buche |
| Publisher | : Springer Nature |
| Total Pages | : 450 |
| Release | : |
| Genre | : |
| ISBN | : 3031550153 |
| Author | : Vieri Giuliano Santucci |
| Publisher | : Frontiers Media SA |
| Total Pages | : 286 |
| Release | : 2020-02-19 |
| Genre | : |
| ISBN | : 288963485X |
| Author | : Satoru Goto |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 276 |
| Release | : 2011-06-09 |
| Genre | : Technology & Engineering |
| ISBN | : 9533071605 |
Robot arms have been developing since 1960's, and those are widely used in industrial factories such as welding, painting, assembly, transportation, etc. Nowadays, the robot arms are indispensable for automation of factories. Moreover, applications of the robot arms are not limited to the industrial factory but expanded to living space or outer space. The robot arm is an integrated technology, and its technological elements are actuators, sensors, mechanism, control and system, etc.
| Author | : Hayit Greenspan |
| Publisher | : Springer Nature |
| Total Pages | : 783 |
| Release | : 2023-09-30 |
| Genre | : Computers |
| ISBN | : 3031439961 |
The ten-volume set LNCS 14220, 14221, 14222, 14223, 14224, 14225, 14226, 14227, 14228, and 14229 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023. The 730 revised full papers presented were carefully reviewed and selected from a total of 2250 submissions. The papers are organized in the following topical sections: Part I: Machine learning with limited supervision and machine learning – transfer learning; Part II: Machine learning – learning strategies; machine learning – explainability, bias, and uncertainty; Part III: Machine learning – explainability, bias and uncertainty; image segmentation; Part IV: Image segmentation; Part V: Computer-aided diagnosis; Part VI: Computer-aided diagnosis; computational pathology; Part VII: Clinical applications – abdomen; clinical applications – breast; clinical applications – cardiac; clinical applications – dermatology; clinical applications – fetal imaging; clinical applications – lung; clinical applications – musculoskeletal; clinical applications – oncology; clinical applications – ophthalmology; clinical applications – vascular; Part VIII: Clinical applications – neuroimaging; microscopy; Part IX: Image-guided intervention, surgical planning, and data science; Part X: Image reconstruction and image registration.
| Author | : Long Jin |
| Publisher | : Frontiers Media SA |
| Total Pages | : 301 |
| Release | : 2024-07-24 |
| Genre | : Science |
| ISBN | : 2832552013 |
Neural network control has been a research hotspot in academic fields due to the strong ability of computation. One of its wildly applied fields is robotics. In recent years, plenty of researchers have devised different types of dynamic neural network (DNN) to address complex control issues in robotics fields in reality. Redundant manipulators are no doubt indispensable devices in industrial production. There are various works on the redundancy resolution of redundant manipulators in performing a given task with the manipulator model information known. However, it becomes knotty for researchers to precisely control redundant manipulators with unknown model to complete a cyclic-motion generation CMG task, to some extent. It is worthwhile to investigate the data-driven scheme and the corresponding novel dynamic neural network (DNN), which exploits learning and control simultaneously. Therefore, it is of great significance to further research the special control features and solve challenging issues to improve control performance from several perspectives, such as accuracy, robustness, and solving speed.
| Author | : De-Shuang Huang |
| Publisher | : Springer Nature |
| Total Pages | : 548 |
| Release | : |
| Genre | : |
| ISBN | : 981975609X |
