Conference Paper RDF
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- Deep Learning Based Receivers for IEEE 802.11p Standard with High Power Amplifiers Distortions
- Deep learning for ocean remote sensing: an application of convolutional neural networks for super-resolution on satellite-derived SST data
- Deep learning framework for infiltrative lung disease classification
- Deep Learning Semantic Compression: IoT Support over LORA Use Case
- Deep reinforcement learning for smart queue management
- Deep Spiking Convolutional Neural Network for Single Object Localization Based On Deep Continuous Local Learning
- Defeating pharming attacks at the client-side
- Defect Characterization on Complex Shape Aeronautical Parts via 3D Point Cloud Processing
- Defending against nodes replication attacks on wireless sensor networks
- Definition of digital twin network adta model in the context of edge-Cloud continuum
- Definitions of engagement in human-agent interaction
- Deformable Shape Retrieval using Bag-of-Feature techniques
- Deformable shape retrieval using bag-of-feature techniques
- Deghosting method for multiple target tracking in a single frequency network
- Delay Analysis and Queue-Length Distribution of a Slotted Metro Network Using Embedded DTMC
- Delay Analysis of the BFT Blockchain Data Dissemination: Case of Narwhal Protocol
- Delay and capacity analysis of structured P2P overlay for IP telephony
- Delayed dynamical system strongly coupled to a nonlinear energy sink: application to machining chatter
- Delta Carrier Range algorithm for indoor positioning application to pseudolite-like transmitters
- DEM Simulation of Granular Flows on a Heap
- DEM Simulation of Granular Flows on a Heap
- Demand estimation adapted to hyperconnected transport systems in regional areas
- Demo Abstract: End-to-end Root Cause Analysis of a Mobile Network
- Demo: ComDeX Unveiled Demonstrating the Future of IoT-Enhanced Communities
- Demodulation of RF signal aggregating four non-contiguous frequency carriers
- Demonstrating intelligent crawling and archiving of web applications
- Demonstrating ProApproX 2.0
- Demonstrating the need of taking into account the compatibility tackifier/resin, and processing conditions to control mechanical properties of RTM CFRP
- Demonstration of a Compositional Learning Framework for Open and Disaggregated Optical Network Control
- Demonstration of ML-aided Impairment-aware L0 Path Computation in Fully Disaggregated Multi-vendor Optical Transport Networks