… a recurrent neural network into the original transformer. In addition, the structure of dual paths
makes … And we embed this improved transformer into a dualpath network, which makes our …

… We propose the DPCTN network based on the traditional … a dual backbone network consisting
of CNN and Transformer … To enhance the network’s understanding of complex scenarios, …

… dual-path object extraction network that combines the strengths of CNN and Transformer. …
We propose a novel dual-path object extraction network that combines the strengths of CNN …

… In this paper, we train a transformer-based neural network to enhance the final CT image …
Further, we feed \(X_{L_t}\) and \(X_{H_f}\) into a modified transformer with three encoders and …

… This paper proposes a dual-path transformer-based full-band and sub-band fusion
network (… The intra and inter parts of the dual-path transformer model sub-band and full-band …

… This paper presents OccFormer, a dual-path transformer network to effectively process the
3D volume for semantic occupancy prediction. OccFormer achieves a long-range, dynamic, …

… transformer, we proposed a dual-path segmentation network combining CNN and transformer
… Firstly, inspired by the ResNet34 [30] network, we designed a lightweight CNN as one of …

… 2) Comparison of ablation experiments in Task 1 In Task 1, we investigate the effects of
various hyperparameters and network structures on the Dual-Path Transformer Network (DPTN) …

… pose DPTNet (Dual-Path Transformer Network), a … network with a powerful self-attention
mechanism to provide complementary clues between the attention path and convolutional path. …

… challenge of solely relying on the Transformer’s self-attention … we present DPTNet (Dual-Path
Transformer Network), which … (1) We introduce a dual-path hierarchical backbone to enable …