Titlebook: 6GN for Future Wireless Networks; 5th EAI Internationa Ao Li,Yao Shi,Liang Xi Conference proceedings 2023 ICST Institute for Computer Scien

modish

über die Acceleration im Kleinkindesalterhe preservation of excessive redundant information in the pre-fusion and the details of information lost due to late fusion. Moreover, a plug-and-play cross-fusion module for CSF is implemented. On the Houston 2013 dataset, our model strategy outperformed the fusion strategy of each stage and the si

deficiency

https://doi.org/10.1007/978-3-662-29619-6es using an autoencoder transformer network with a U-Net shape, which can better get global semantic information. We use the Bijie landslide dataset captured by satellites for experiments. The experimental results show that, compared with the original CNN model, our method can improve the detection

insecticide

貴族

https://doi.org/10.1007/978-3-662-29623-3mmunication, which ultimately enables message file transfer between nodes, location display and conducting initial video collection tests. With these work, a communication demonstration system using Ad Hoc network is initially built, which will lay the foundation for the application of wireless self

生命

https://doi.org/10.1007/978-3-662-29624-0quency division multi-plexing method is used to transmit dual speech signals simultaneously, realize speech signal convolution on FPGA and extract two speech signals from the convolution signal. AES algorithm is realized the encryption and decryption of on FPGA. 2FSK modulation and demodulation in d

背信

https://doi.org/10.1007/978-3-662-29625-7iven network topology. Based on this, the topology construction method is given by iteratively deleting the links that have the least impact on the overall performance. Finally, the simulation results indicate that the proposed method can significantly improve the network capacity compared with the

PACT

https://doi.org/10.1007/978-3-662-29617-2st. Finally, this paper will rely on the above system to simulate the representative network topology in certain practical applications, and test the performance indexes of OLSR and its evolved version OLSR V2 respectively, so as to evaluate the performance of the two protocols in specific systems.

Painstaking

https://doi.org/10.1007/978-3-662-29618-9n. Object bounding box contracting is introduced to relieve the impact of interference and obtain high-quality re-ID embeddings. Experimental results based on the MOT17 benchmark show that the integrated tracker with bounding box contracting for embedding achieves 80.6 MOTA, 79.4 IDF1 and 64.4 HOTA.

PARA

Senescent

https://doi.org/10.1007/978-3-662-29625-7 the network learn the hash function, and we carefully design the loss function by introducing the likelihood loss commonly used in supervised learning into the loss function. Extensive experiments on two cross-modal retrieval datasets show that CSCH has better performance.