@inproceedings{10769185,

title = {Exploitation of Open Source Datasets and Deep Learning Models for the Detection of Objects in Urban Areas},

author = {Elpida Gkouvra and Thodoris Betsas and Maria Pateraki},

doi = {10.1109/ICIPCW64161.2024.10769185},

year  = {2024},

date = {2024-10-01},

booktitle = {2024 IEEE International Conference on Image Processing Challenges and Workshops (ICIPCW)},

pages = {4103-4108},

abstract = {In this work we utilize different open-source datasets and deep learning models for detecting objects from image data captured by a mobile mapping system integrating the multi-camera Ladybug 5+1 in an urban area. In our experiments we exploit sets of pre-trained models and models trained via transfer learning techniques with available open source datasets for object detection, semantic-, instance-, and panoptic segmentation. Tests with the trained models are performed with image data from the Ladybug 5+ camera.},

keywords = {Cameras, Conferences, Context modeling, Data models, deep learning, deep learning models, Image segmentation, mobile mapping, Object detection, open-source datasets, Training, Transfer learning, Urban areas},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{9657125,

title = {Cloud for Holography and Augmented Reality},

author = {Antonios Makris and Abderrahmane Boudi and Massimo Coppola and Lu\'{i}s Cordeiro and Massimiliano Corsini and Patrizio Dazzi and Ferran Diego Andilla and Yago Gonz\'{a}lez Rozas and Manos Kamarianakis and Maria Pateraki and Thu Le Pham and Antonis Protopsaltis and Aravindh Raman and Alessandro Romussi and Lu\'{i}s Rosa and Elena Spatafora and Tarik Taleb and Theodoros Theodoropoulos and Konstantinos Tserpes and Enrico Zschau and Uwe Herzog},

doi = {10.1109/CloudNet53349.2021.9657125},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {2021 IEEE 10th International Conference on Cloud Networking (CloudNet)},

pages = {118-126},

abstract = {The paper introduces the CHARITY framework, a novel framework which aspires to leverage the benefits of intelligent, network continuum autonomous orchestration of cloud, edge, and network resources, to create a symbiotic relationship between low and high latency infrastructures. These infrastructures will facilitate the needs of emerging applications such as holographic events, virtual reality training, and mixed reality entertainment. The framework relies on different enablers and technologies related to cloud and edge for offering a suitable environment in order to deliver the promise of ubiquitous computing to the NextGen application clients. The paper discusses the main pillars that support the CHARITY vision, and provide a description of the planned use cases that are planned to demonstrate CHARITY capabilities.},

keywords = {Cloud computing, Conferences, Entertainment industry, Intelligent networks, Mixed reality, Symbiosis, Training},

pubstate = {published},

tppubtype = {inproceedings}

}