The larger the value, the more similar the SSIM is, and the maximum value is 1 entropy: it reflects the amount of average information in the image. To validate and evaluate the performance of the present cycleSimulationGAN, two additional approaches were carried out for comparison purpose ...
代表了 outer products # -*- coding: utf-8 -*-importtensorflowastfimportnumpyasnpdefglobal_average_pool(x):c=x.get_shape()[-1]returntf.reshape(tf.reduce_mean(x,axis=[1,2]),(-1,1,1,c))defchannel_wise_attention(inputs,hidden_states,k):inputs_shape=map(lambdax:x.value,inputs.sh...
To assess the verity of the proposed identification method, two well-known datasets were chosen, where the proposed method shows the best average accuracies of 98.55% and 99.84% on the EEGMMIDB and DEAP dataset, respectively. The experimental results demonstrate the superiority of the proposed ...
Notice that the most popular region proposal network (RPN) backbone has achieved over 95% recall rate on the KITTI 3D Detection Benchmark, whereas this method only achieves 78% Average Precision (AP). The reason for such a gap stems from the difficulty in encoding an object and extracting th...
In particular, SAMformer surpasses TSMixer by 14.33 % on average, while having ∼ 4 times fewer parameters, and iTransformer and PatchTST by 6.58 % and 8.79 % respectively. Architecture SAMformer takes as input a D -dimensional time series of length L (look-back window), arranged in a ...
Evaluated by our validation sets on the server, the pruned YOLOv3 saves 79.7% floating point operations (FLOPs), 93.8% parameter size, 93.8% model volume and 45.4% inference times with only 4.16% mean of average precision (mAP) loss. Evaluated on the embedded device, the pruned model ...
tive region, or “soft” pooling that averages the spatial fea- tures with attentive weights. As for VQA, Zhu et al. [43] adopted the “soft” attention to merge image region fea- tures. To further refine the spatial attention, Yang et al. [35] and Xu et al. [33] applied a ...
The results show that using the proposed algorithm, the average uncoded BER of the last data block in one frame is much lower than the BER yielded by the forward-only tracking method and is only sightly higher than the BER of the first data block.Index Terms--Channel estimation, time-...
This paper presents a channel-wise average pooling and one dimension pixel-shuffle architecture for a denoising autoencoder (CPDAE) design that can be applied to efficiently remove electrode motion (EM) artifacts in an electrocardiogram (ECG) signal. The three advantages of the proposed design are...
Taking global pooling as an example, the commonly used softmax classifier averages the input image [8,11], preserving its overall details and location, but leads to overfitting to postures and overlooking potential information. Some attempts address this issue by expanding the receptive field [15]...