no code implementations • 29 Jan 2024 • Adane Nega Tarekegn, Mohib Ullah, Faouzi Alaya Cheikh
Multi-label learning is a rapidly growing research area that aims to predict multiple labels from a single input data point.
no code implementations • 11 Jun 2020 • Mohib Ullah, Maqsood Mahmud, Habib Ullah, Kashif Ahmad, Ali Shariq Imran, Faouzi Alaya Cheikh
For multi-target tracking, target representation plays a crucial rule in performance.
no code implementations • 7 Oct 2019 • Kashif Ahmad, Konstantin Pogorelov, Mohib Ullah, Michael Riegler, Nicola Conci, Johannes Langguth, Ala Al-Fuqaha
In this paper we present our methods for the MediaEval 2019 Mul-timedia Satellite Task, which is aiming to extract complementaryinformation associated with adverse events from Social Media andsatellites.
no code implementations • 7 May 2019 • Muhammad Bilal, Mohib Ullah
We trained L2 regularized sparse autoencoder end-to-end for reducing the size of the feature vector to handle the classic problem of the curse of dimensionality in chemometric data analysis.