인공지능기반무선측위기술동향및전망
차경주， 이정범， 이웅희 - 전자공학회논문지, 2022 - dbpia.co.kr
최근 정보통신 및 인공지능 기술의 거듭된 발전은 자율 주행, 디지털 트윈, 가상 현실을 비롯한
다양한 실용 분야 현실화를 가속하고 있으며, 고도의 무선 측위 기술은 이러한 최첨단 기술 연구 …
다양한 실용 분야 현실화를 가속하고 있으며, 고도의 무선 측위 기술은 이러한 최첨단 기술 연구 …
Deep Reinforcement Learning-based Quantization for Federated Learning
Federated learning (FL) is a promising solution to harness the advances of machine
learning under the premise of privacy security, whereas the communication overhead of …
learning under the premise of privacy security, whereas the communication overhead of …
Dynamic DNN Nodes Drop-out Rate Analysis
Y Gao - 2021 3rd International Conference on Machine …, 2021 - ieeexplore.ieee.org
The Dropout method is very useful when dealing with the overfitting problem that occurs
during the training process of a data set whose data size is in the range thousands to tens of …
during the training process of a data set whose data size is in the range thousands to tens of …
Federated Learning Based User Scheduling for Real-Time Multimedia Tasks in Edge Devices
W Wen, Y Liu, Y Gao, Z Zhu, Y Shi, X Peng - International Conference on …, 2022 - Springer
Edge networks are highly volatile and the quality of device communication and
computational resources change not only over time but also according to the movement of …
computational resources change not only over time but also according to the movement of …
Deep Recurrent Q Networks for Dynamic Spectrum Access in Dynamic Heterogeneous Envirnments with Partial Observations
Y Xu - 2022 - vtechworks.lib.vt.edu
Abstract Dynamic Spectrum Access (DSA) has strong potential to address the need for
improved spectrum efficiency. Unfortunately, traditional DSA approaches such as simple" …
improved spectrum efficiency. Unfortunately, traditional DSA approaches such as simple" …
[PDF][PDF] Machine Learning for Reliable Communication and Improved Tracking of Dynamical Systems
KP Vedula - PhD diss., WORCESTER POLYTECHNIC INSTITUTE, 2020 - digital.wpi.edu
Reliable communication systems and optimal tracking of dynamic systems are subjects that
have been studied for several decades. In recent years, however, there is a renewed interest …
have been studied for several decades. In recent years, however, there is a renewed interest …
[PDF][PDF] Федеративное обучение (FL)–Обзор
М Аль-Тамими, МБ Хассан, СА Аббас - Изв. СПбГЭТУ «ЛЭТИ, 2024 - izv.etu.ru
Рассмотрены основные аспекты федеративного обучения (FL) в контексте систем
обнаружения вторжений (IDS) в сетях интернета вещей (IoT). Федеративное обучение …
обнаружения вторжений (IDS) в сетях интернета вещей (IoT). Федеративное обучение …
A Unified Linear Speedup Analysis of Federated Averaging and Nesterov FedAvg
Federated learning (FL) learns a model jointly from a set of participating devices without
sharing each other's privately held data. The characteristics of non-iid data across the …
sharing each other's privately held data. The characteristics of non-iid data across the …
[引用][C] 음성신호전송을위한저복잡도의의미론적통신시스템
여예린， 김정현， 송홍엽 - 한국통신학회학술대회논문집, 2022 - dbpia.co.kr
요 약본 논문은 통신 시스템에서 음성 신호의 의미적인 정보를 효율적으로 복구하는 모델에
대해서 다룬다. SE-ResNet 모듈을 사용하는 기존 DeepSC-S-SER 모델은 좋은 성능을 갖지만 …
대해서 다룬다. SE-ResNet 모듈을 사용하는 기존 DeepSC-S-SER 모델은 좋은 성능을 갖지만 …