Downloads provided by UsageCounts
This document describes the initial version of the methodologies pro- posed by MARVEL partners towards the realisation of the Audio, Visual and Multimodal AI Subsystem of the MARVEL architecture. These include methods for Sound Event De- tection, Sound Event Localisation and Detection, Automated Audio Captioning, Visual Anomaly Detection, Visual Crowd Counting, Audio-Visual Crowd Counting, as well as methodologies for improving the training and efficiency of AI models under supervised, unsupervised, and cross-modal contrastive learning settings. The effectiveness of these methods is compared against recent baselines, towards achieving the AI methodology- related objectives of the MARVEL project.
E2F2C, smart cities, AI, multimodal, unsupervised, supervised, cross-modal
E2F2C, smart cities, AI, multimodal, unsupervised, supervised, cross-modal
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 18 | |
| downloads | 68 |

Views provided by UsageCounts
Downloads provided by UsageCounts