… is the motivation behind using this neural network in this work. This network is having an …
Moreover, this section explains the constraints for deep learning in surveillance and how we …

… use of transfer learning via neural networks and statistical k-… class are available, ie, they
struggle with continual learning and … in video analysis. We observe that even with relatively small …

… for large geographical area monitoring for public security, intelligent … the sensor for integrated
video analytics. In many IoVT … In this article, we have introduced an emerging class of IoT …

… learning methods, in particular Deep Neural Networks (DNNs… on machine learning models
in potentially security-critical … used for data analysis and machine learning, we developed the …

… by implementing a well-known convolutional neural network (… While in the Binary, we consider
all 13 abnormal events as one class … Tang, YP; Wang, XJ; Lu, HF Intelligent video analysis …

… and analysis of tools and methods for analysis of such large … through analytics can be a
critical enabler for executing the … only collected from clinical record, tele-monitoring or medical …

… -based video analysis and retrieval, visual surveillance, Human–… classification and the
predicted class labels can be analyzed and … with CNN-Recurrent Neural Network (RNN) network. …

… places, there has been a surge in research outputs on video analysis and anomaly … network
estimates the posterior probability of observing a class label from a set of normal class labels …

… the important approaches for video sequential data learning using deep learning since video
data analytics required both spatial and temporal features for its analysis. The mainstream …

… smart city video surveillance [39]. One of the popular applications of video analysis is crowd
… , in which images are classified based on the features belonging to a particular class. In the …