Search Results for author:
Found 8 papers, 4 papers with code
VID-WIN: Fast Video Event Matching with Query-Aware Windowing at the Edge for the Internet of Multimedia Things
Presently, many window optimization techniques have been proposed in event processing with an underlying assumption that the incoming stream has a structured data model.
Donut visualizations for network-level and regional-level overview of Spatial Social Networks
Spatial Social Networks (SSN) build on the node and edge structure used in Social Network Analysis (SNA) by incorporating spatial information.
Social and Information Networks Computers and Society
MuSeM: Detecting Incongruent News Headlines using Mutual Attentive Semantic Matching
On the other hand, more recent works that use headline guided attention to learn a headline derived contextual representation of the news body also result in convoluting overall representation due to the news body's lengthiness.
Visual Semantic Multimedia Event Model for Complex Event Detection in Video Streams
The paper contribution is threefold: i) we present a knowledge graph representation for multimedia streams, ii) a hierarchical event network to detect visual patterns from media streams and iii) define complex pattern rules for complex multimedia event reasoning using event calculus
VidCEP: Complex Event Processing Framework to Detect Spatiotemporal Patterns in Video Streams
Current CEP systems have inherent limitations to query video streams due to their unstructured data model and lack of expressive query language.
Knowledge Graph Driven Approach to Represent Video Streams for Spatiotemporal Event Pattern Matching in Complex Event Processing
We propose the Video Event Knowledge Graph (VEKG), a graph driven representation of video data.
Traffic Prediction Framework for OpenStreetMap using Deep Learning based Complex Event Processing and Open Traffic Cameras
The lack of an open-source traffic estimation method using open data platforms is a bottleneck for building sophisticated navigation services on top of OpenStreetMap (OSM).
Human Assisted Artificial Intelligence Based Technique to Create Natural Features for OpenStreetMap
In this work, we propose an AI-based technique using freely available satellite images like Landsat and Sentinel to create natural features over OSM in congruence with human editors acting as initiators and validators.
