How often does the letter r occur in:
We are living in a world where we are surrounded by so many intelligent surveillance systems. These surveillance systems capture data about how we live and what we do. One of the biggest complaints regarding surveillance has been its inability to correctly identify different objects or different activity in situations which appear trivial to the human observer. The security industry remains interested in capturing actionable data from intelligent video and sensory surveillance systems and this year we saw increasing interest from non-security industries. Particularly, with the popularity of large-scale sensor and visual surveillance, videos captured by static and dynamic cameras or information sensed by different sensors are required to be automatically analyzed.
For example, convolutional neural networks have demonstrated superiority on modeling high-level visual concepts, while recurrent neural networks have shown promise in modeling temporal dynamics. Human behavior analysis with deep learning is becoming an emerging research area in the field of intelligent surveillance. The goal of this special issue is to call for a coordinated effort to understand the opportunities and challenges emerging in intelligent surveillance with deep learning techniques.
This special issue aims to provide a platform for the research community and professionals to demonstrate solutions and address research challenges in visual and sensory data processing for real time intelligent surveillance systems. Further, diffusion of visual and sensory data for intelligent surveillance systems will open new horizons and research domains that may be of interest to readers and the research community. This special issue aims at publishing high-quality manuscripts covering new research on topics related to implementation of visual and sensory data processing for real time intelligent surveillance systems. The special issue will offer a timely collection of research updates to benefit researchers and practitioners working in the broad area of image and video processing using deep learning.

user
The text includes one hundred and twenty-nine "r"s in total.
assistant