activity
20182022
most citedFederated Self-Supervised Learning of Multi-Sensor Representations for Embedded Intelligence

104 citations · 107 across the 4 of their papers we have counts for

collaborators

6 papers

eess.SP2022

Intelligent Blockage Recognition using Cellular mmWave Beamforming Data: Feasibility Study

Bram van Berlo, Yang Miao, Rizqi Hersyandika +4

Joint Communication and Sensing (JCAS) is envisioned for 6G cellular networks, where sensing the operation environment, especially in presence of humans, is as important as the hig…

cs.LG20221 cited

Privacy-preserving Speech Emotion Recognition through Semi-Supervised Federated Learning

Vasileios Tsouvalas, Tanir Ozcelebi, Nirvana Meratnia

Speech Emotion Recognition (SER) refers to the recognition of human emotions from natural speech. If done accurately, it can offer a number of benefits in building human-centered c…

eess.SP20202 cited

Millimeter Wave Sensing: A Review of Application Pipelines and Building Blocks

Bram van Berlo, Amany Elkelany, Tanir Ozcelebi +1

The increasing bandwidth requirement of new wireless applications has lead to standardization of the millimeter wave spectrum for high-speed wireless communication. The millimeter…

cs.LG2020104 cited

Federated Self-Supervised Learning of Multi-Sensor Representations for Embedded Intelligence

Aaqib Saeed, Flora D. Salim, Tanir Ozcelebi +1

Smartphones, wearables, and Internet of Things (IoT) devices produce a wealth of data that cannot be accumulated in a centralized repository for learning supervised models due to p…

cs.LG2019

Multi-task Self-Supervised Learning for Human Activity Detection

Aaqib Saeed, Tanir Ozcelebi, Johan Lukkien

Deep learning methods are successfully used in applications pertaining to ubiquitous computing, health, and well-being. Specifically, the area of human activity recognition (HAR) i…

cs.LG2018

Learning behavioral context recognition with multi-stream temporal convolutional networks

Aaqib Saeed, Tanir Ozcelebi, Stojan Trajanovski +1

Smart devices of everyday use (such as smartphones and wearables) are increasingly integrated with sensors that provide immense amounts of information about a person's daily life s…