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Found 13 papers, 5 papers with code
Towards Enabling FAIR Dataspaces Using Large Language Models
Dataspaces have recently gained adoption across various sectors, including traditionally less digitized domains such as culture.
NeuSyRE: Neuro-Symbolic Visual Understanding and Reasoning Framework based on Scene Graph Enrichment
We present a loosely-coupled neuro-symbolic visual understanding and reasoning framework that employs a DNN-based pipeline for object detection and multi-modal pairwise relationship prediction for scene graph generation and leverages common sense knowledge in heterogenous knowledge graphs to enrich scene graphs for improved downstream reasoning.
Ranked #1 on
Scene Graph Generation
on Visual Genome
(mR@100 metric)
Climate-Resilient UAVs: Enhancing Energy-Efficient B5G Communication in Harsh Environments
This paper explores the crucial role of Unmanned Aerial Vehicles (UAVs) in advancing Beyond Fifth Generation (B5G) communication networks, especially in adverse weather conditions like rain, fog, and snow.
Blockchain as an Enabler for Transfer Learning in Smart Environments
The knowledge, embodied in machine learning models for intelligent systems, is commonly associated with time-consuming and costly processes such as large-scale data collection, data labelling, network training, and fine-tuning of models.
UnseenNet: Fast Training Detector for Any Unseen Concept
Our model (UnseenNet) is trained on the ImageNet classification dataset for unseen classes and tested on an object detection dataset (OpenImages).
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.
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.
Word Re-Embedding via Manifold Dimensionality Retention
Word embeddings seek to recover a Euclidean metric space by mapping words into vectors, starting from words co-occurrences in a corpus.
