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Search Results - technology+classifications+%3e+3.+computer+science
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OffloaDNN: Shaping DNNs for Scalable Offloading of Computer Vision Tasks at the Edge
OffloaDNN enhances mobile CV task execution by optimizing DNN layers, reducing memory use by 82.5%, and increasing task handling by 26.9% Copy Image URL via instructions below https://nu.testtechnologypublisher.com/files/sites/mark-saulich-23.jpg Background: The computational demands of deep neural networks (DNNs) for computer vision (CV)...
Published: 9/10/2024
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Inventor(s):
Francesco Restuccia
,
Tanzil Hassan
,
Carla Fabiana Chiasserini
,
Corrado Puligheddu
,
Nancy Varshney
Keywords(s):
Computational Offloading
,
Edge devices
,
Resource allocation
Category(s):
Technology Classifications > 3. Computer Science
SAWEC: Sensing-Assisted Wireless Edge Computing
Sensing-Assisted Wireless Edge Computing (SAWEC) enhances mobile device performance by offloading computational tasks to edge servers, reducing video data transmission through intelligent filtering, and optimizing bandwidth usage. This innovative approach ensures faster processing times and lower latency for real-time applications. Copy Image URL...
Published: 9/10/2024
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Inventor(s):
Francesco Restuccia
,
Khandaker Foysal Haque
,
Francesca Meneghello
,
Md Ebtidaul Karim
Keywords(s):
Category(s):
Technology Classifications > 3. Computer Science
Faster and Accurate Neural Networks with Semantic Inference
SINF intelligently clusters inputs to selectively engage DNN subgraphs, reducing computational load while maintaining high accuracy. Copy Image URL via instructions below https://nu.testtechnologypublisher.com/files/sites/mark-saulich-21.jpg Background The deployment of Deep Neural Networks in real-world applications faces significant challenges...
Published: 9/10/2024
|
Inventor(s):
Francesco Restuccia
,
Jonathan Ashdown
,
A Q M Sazzad Sayyed
Keywords(s):
Artificial intelligence
,
computer vision and deep learning
,
Efficient computing
Category(s):
Technology Classifications > 3. Computer Science
Methods for real-time wideband RF waveform and emission classification
Revolutionary deep learning tech for accurate, real-time spectrum sensing of wireless signals like 5G, WiFi, and Bluetooth Copy Image URL via instructions below https://nu.testtechnologypublisher.com/files/sites/mark-saulich-17.jpg Background: Spectrum sensing is crucial in wireless communications for efficiently utilizing the limited available...
Published: 9/10/2024
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Inventor(s):
Tommaso Melodia
,
Milin Zhang
,
Salvatore D'Oro
,
Daniel Uvaydov
,
Francesco Restuccia
,
Clifton Robinson
Keywords(s):
Deep learning
,
O-RAN
,
Spectrum sensing
Category(s):
Technology Classifications > 3. Computer Science
SiMWiSense: Simultaneous Multi-Subject Activity Classification Through Wi-Fi Signals
SiMWiSense uses Wi-Fi Channel State Information (CSI) and a few-shot learning algorithm to classify activities of multiple subjects simultaneously, overcoming scalability issues and enhancing generalization with minimal data. Copy Image URL via instructions below https://nu.testtechnologypublisher.com/files/sites/mark-saulich-.jpg Background:...
Published: 9/10/2024
|
Inventor(s):
Francesco Restuccia
,
Khandaker Foysal Haque
,
Milin Zhang
Keywords(s):
Category(s):
Technology Classifications > 3. Computer Science
I Sense Your Feedback: Rethinking Wi-Fi Sensing Through MU-MIMO Beamforming Feedback Learning
BeamSense uses MU-MIMO beamforming feedback for high-granularity Wi-Fi sensing, enhanced by a Few-Shot Learning algorithm for quick adaptation to new environments with minimal data. Copy Image URL via instructions below https://nu.testtechnologypublisher.com/files/sites/mark-saulich-7.jpg Background: The demand for accurate and granular...
Published: 9/10/2024
|
Inventor(s):
Francesco Restuccia
,
Khandaker Foysal Haque
,
Milin Zhang
Keywords(s):
Category(s):
Technology Classifications > 3. Computer Science
3D-O-RAN: Dynamic Data Driven Open Radio Access Network Systems
3D-O-RAN enhances O-RAN with semantic slicing and dynamic neural certification for cost-effective, interoperable network performance Copy Image URL via instructions below https://nu.testtechnologypublisher.com/files/sites/mark-saulich-13.jpg Background In the rapidly evolving landscape of cellular communications, the need for systems that...
Published: 9/10/2024
|
Inventor(s):
Francesco Restuccia
,
Erik Blasch
,
Jonathan Ashdown
,
Kurt Turck
Keywords(s):
Category(s):
Technology Classifications > 3. Computer Science
SEM-O-RAN: Semantic NextG O-RAN Slicing for Data-Driven Edge-Assisted Mobile Applications
SEM-O-RAN uses O-RAN architecture and semantic compression to offload ML tasks to the edge, optimizing network resources and reducing latency. Copy Image URL via instructions below https://nu.testtechnologypublisher.com/files/sites/mark-saulich-16.jpg Background The exponential growth in the number of connected devices and the increasingly...
Published: 9/10/2024
|
Inventor(s):
Corrado Puligheddu
,
Francesco Restuccia
,
Carla Fabiana Chiasserini
Keywords(s):
5G and beyond
,
5G Networks
,
6G
,
Deep learning
,
Machine Learning
,
Mobile devices
,
O-RAN
,
Semantics
,
Software-defined Networks
Category(s):
Technology Classifications > 3. Computer Science
V-Edge: Enabling Vehicular Edge Intelligence in Unlicensed Spectrum Bands
V-Edge enhances vehicular intelligence using 60 GHz and sub-6 GHz technologies for low-latency, high-throughput, real-time AI processing Copy Image URL via instructions below https://nu.testtechnologypublisher.com/files/sites/mark-saulich-15.jpg Background: As the landscape of vehicular technology evolves, the integration of AI and DL within...
Published: 9/10/2024
|
Inventor(s):
Francesco Raviglione
,
Francesco Restuccia
,
Claudio Casetti
Keywords(s):
Category(s):
Technology Classifications > 3. Computer Science
SplitBeam: Rethinking Beamforming Feedback in MU-MIMO Wi-Fi Systems Through Split Neural Networks
SplitBeam uses a split deep neural network to optimize Wi-Fi beamforming, improving connectivity and reducing interference by processing the channel state information matrix with machine learning. Copy Image URL via instructions below https://nu.testtechnologypublisher.com/files/sites/mark-saulich-9.jpg Background: Contemporary Wi-Fi networks...
Published: 9/10/2024
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Inventor(s):
Niloofar Bahadori
,
Francesco Restuccia
,
Marco Levorato
,
Yoshitomo Matsubara
Keywords(s):
Deep learning
,
MU-MIMO
,
Split Computing
,
Wi-Fi
Category(s):
Technology Classifications > 3. Computer Science
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