| 000 | 03553nam a22003735i 4500 | ||
|---|---|---|---|
| 001 | 395206 | ||
| 003 | ES-MaUEC | ||
| 005 | 20230110120132.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 210729s2022 sz | s |||| 0|eng d | ||
| 020 | _a9783030704513 | ||
| 024 | 7 |
_a10.1007/978-3-030-70451-3 _2doi |
|
| 040 |
_aES-MaUEC _bspa _cES-MaUEC |
||
| 050 | 4 |
_aTK7872.D48 _b2022 EB |
|
| 245 | 1 | 0 |
_a4th EAI International Conference on Robotic Sensor Networks _cedited by Shenglin Mu, Li Yujie, Huimin Lu. |
| 250 | _a1st edition 2022 | ||
| 264 | 1 |
_aCham _bSpringer International Publishing _c2022 |
|
| 300 |
_a1 recurso en línea (X, 132 páginas) _b75 ilustraciones, 56 ilustraciones a color |
||
| 336 |
_atexto _btxt _2rdacontent |
||
| 337 |
_aelectrónico _bc _2rdamedia |
||
| 338 |
_arecurso electrónico _bcr _2rdacarrier |
||
| 347 |
_aarchivo de texto _bPDF |
||
| 490 | 0 |
_aEAI/Springer Innovations in Communication and Computing _x2522-8609 |
|
| 505 | 0 | _aIntroduction -- A Mobile Robotic System for Rescue and Surveillance in Indoor Environment -- Study on the Learning in Intelligent Control using Neural Networks based on Back-Propagation and Differential Evolution -- Word Sense Disambiguation Graph-Based and Knowledge Base -- GDP Carbon Emission Prediction Base on Grey Model and Neural Network -- Automatic optimization of YOLOV3 image classification and positioning based on particle swarm optimization algorithm -- Contour Mask and Matting Driven Face Image Generation -- Eye-interface System using Convolutional Neural Networks for People with Physical Disabilities -- Proposal of Omnidirectional Movable Positioning Plate Using T-shaped Omni Wheel -- A general pseudo-random number generator based on chaos -- A Light chaotic encryption algorithm for real-time video encryption -- Intelligent Analysis and Presentation of IOT Image Collection in Private Cloud -- Conclusion. | |
| 520 | _aThis book presents papers presented at the 4th EAI International Conference on Robotic Sensor Networks. The conference explored the integration of networks and robotic technologies, which has become a topic of increasing interest for both researchers and developers from academic fields and industries worldwide. The authors explore how big networks are becoming the main tool for the next generation of robotic research, owing to the explosive number of networks models and the increased computational power of computers. The papers discuss how these trends significantly extend the number of potential applications for robotic technologies while also bringing new challenges to the networks' communities. The 2nd EAI International Conference on Robotic Sensor Networks was held online on November 21-22, 2020. Presents the proceedings from 4th EAI International Conference on Robotic Sensor Networks, which took place November 21-22, 2020; Features papers on topics ranging from robotics in medicine to robotics in rescue and surveillance; Includes perspectives from a multi-disciplinary selection of global researchers, academics, and professionals. | ||
| 776 | 0 | 8 |
_iPrinted edition: _z9783030704506 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030704520 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030704537 |
| 856 | 4 | 0 |
_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-70451-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid) |
| 942 |
_2lcc _cLE |
||
| 988 | _aSpringer_Engineering_2022 | ||
| 999 |
_c395206 _d395206 |
||