activity
20182026
most citedFeature Extraction for Temporal Signal Recognition: An Overview

13 citations · 31 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

FedUAF: Uncertainty-Aware Fusion with Reliability-Guided Aggregation for Multimodal Federated Sentiment Analysis

Xianxun Zhu, Zezhong Sun, Imad Rida +4

Multimodal sentiment analysis in federated learning environments faces significant challenges due to missing modalities, heterogeneous data distributions, and unreliable client upd…

cs.SD2020★ 1 cited

Data-driven audio recognition: a supervised dictionary approach

Imad Rida

Machine hearing is an emerging area. Motivated by the need of a principled framework across domain applications for machine listening, we propose a generic and data-driven represen…

cs.CV2019★ 13 cited

Forensic shoe-print identification: a brief survey

Imad Rida, Lunke Fei, Hugo Proença +2

As an advanced research topic in forensics science, automatic shoe-print identification has been extensively studied in the last two decades, since shoe marks are the clues most fr…

cs.CV2018★ 4 cited

An efficient supervised dictionary learning method for audio signal recognition

Imad Rida, Romain Hérault, Gilles Gasso

Machine hearing or listening represents an emerging area. Conventional approaches rely on the design of handcrafted features specialized to a specific audio task and that can hardl…

eess.AS2018★ 13 cited

Feature Extraction for Temporal Signal Recognition: An Overview

Imad Rida

Due to the huge progress of the recording devices, data from heterogeneous nature can be recorded, such as spatial, temporal and spatio-temporal. Nowadays, time-based data is of pa…