Downloads provided by UsageCounts
This document describes methodologies proposed by MARVEL partners during the second reporting period of the project towards the realisation of the Au- dio, Visual and Multimodal AI Subsystem of the MARVEL architecture. These meth- odologies complement the methodologies proposed by MARVEL partners during the first reporting period, and include methods for Automated Audio Captioning, Visual Crowd Counting, Visual Anomaly Detection, Audio-Visual Anomaly Detection, Audio- Visual Event Detection, privacy-preserving Audio-Visual Emotion Recognition, as well as methodologies for improving the training of dense regression models for efficient inference on standard and Gigapixel images, and on heavily compressed images. The effectiveness of these methods is compared against recent baselines, towards achieving the AI methodology-related objectives of the MARVEL project.
smart city, E2F2C, AI, audio, multimodal, visual
smart city, E2F2C, AI, audio, multimodal, visual
| 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 | 69 | |
| downloads | 24 |

Views provided by UsageCounts
Downloads provided by UsageCounts