(1) From algorithm perspective, we propose a sparsity inheritance mechanism along with an inherited dynamic pruning (IDP) method to obtain a series of N:M sparse candidate Transformers rapidly.
Integrated access and backhaul (IAB) networks have the potential to provide high data rate in both access and backhaul networks by sharing the same spectrum.
In autonomous driving, accurately estimating the state of surrounding obstacles is critical for safe and robust path planning.
Considering joint transmissions and BS silence strategy, we propose hybrid precoding algorithms which minimize the sum power consumption of the base stations (BSs), for both fully- and partially-connected hybrid precoding (FHP and PHP, respectively) schemes, for single-carrier and orthogonal frequency-division multiplexing systems.
Panoptic segmentation is a complex full scene parsing task requiring simultaneous instance and semantic segmentation at high resolution.
With the increasing size of Deep Neural Network (DNN) models, the high memory space requirements and computational complexity have become an obstacle for efficient DNN implementations.
Results: Here, a very deep neural network, the deep inception-inside-inception networks (Deep3I), is proposed for protein secondary structure prediction and a software tool was implemented using this network.