audio upsampler
上采样器
video upsampler
視訊上采樣器
the upsampler
上采樣器
upsampler module
上采樣模組
upsampler circuit
上采樣電路
digital upsampler
數位上采樣器
upsampler algorithm
上采樣演算法
neural networks use upsamplers to increase the spatial resolution of feature maps.
神經網絡使用上採樣器來提高特徵圖的空間解析度。
the image processing pipeline includes a convolutional upsampler for upscaling.
影像處理流程中包含用於上採樣的卷積上採樣器。
our model employs a learned upsampler to reconstruct high-resolution outputs.
我們的模型採用學習到的上採樣器來重建高解析度輸出。
the upsampler block transforms low-resolution features into dense representations.
上採樣器模塊將低解析度特徵轉換為密集表示。
transposed convolution is commonly used as an upsampler in deep learning architectures.
轉置卷積在深度學習架構中常被用作上採樣器。
the upsampler layer doubles the spatial dimensions of the input tensor.
上採樣器層會將輸入張量的空間維度加倍。
training the upsampler requires balancing reconstruction quality and computational efficiency.
訓練上採樣器需要在重建品質與計算效率之間取得平衡。
the sub-pixel upsampler achieves high-resolution output through efficient channel rearrangement.
子像素上採樣器透過高效的通道重排來實現高解析度輸出。
adaptive upsamplers can learn task-specific upscaling kernels.
自適應上採樣器可以學習特定任務的上採樣核心。
the residual upsampler architecture preserves fine details during upscaling.
殘差上採樣器架構在上採樣過程中保留細節。
the depth-to-space upsampler rearranges channel data into spatial dimensions.
深度到空間上採樣器將通道數據重新排列為空間維度。
our upsampler implementation reduces artifacts in generated images.
我們的上採樣器實現方式可減少生成影像中的瑕疵。
audio upsampler
上采样器
video upsampler
視訊上采樣器
the upsampler
上采樣器
upsampler module
上采樣模組
upsampler circuit
上采樣電路
digital upsampler
數位上采樣器
upsampler algorithm
上采樣演算法
neural networks use upsamplers to increase the spatial resolution of feature maps.
神經網絡使用上採樣器來提高特徵圖的空間解析度。
the image processing pipeline includes a convolutional upsampler for upscaling.
影像處理流程中包含用於上採樣的卷積上採樣器。
our model employs a learned upsampler to reconstruct high-resolution outputs.
我們的模型採用學習到的上採樣器來重建高解析度輸出。
the upsampler block transforms low-resolution features into dense representations.
上採樣器模塊將低解析度特徵轉換為密集表示。
transposed convolution is commonly used as an upsampler in deep learning architectures.
轉置卷積在深度學習架構中常被用作上採樣器。
the upsampler layer doubles the spatial dimensions of the input tensor.
上採樣器層會將輸入張量的空間維度加倍。
training the upsampler requires balancing reconstruction quality and computational efficiency.
訓練上採樣器需要在重建品質與計算效率之間取得平衡。
the sub-pixel upsampler achieves high-resolution output through efficient channel rearrangement.
子像素上採樣器透過高效的通道重排來實現高解析度輸出。
adaptive upsamplers can learn task-specific upscaling kernels.
自適應上採樣器可以學習特定任務的上採樣核心。
the residual upsampler architecture preserves fine details during upscaling.
殘差上採樣器架構在上採樣過程中保留細節。
the depth-to-space upsampler rearranges channel data into spatial dimensions.
深度到空間上採樣器將通道數據重新排列為空間維度。
our upsampler implementation reduces artifacts in generated images.
我們的上採樣器實現方式可減少生成影像中的瑕疵。
探索常見搜尋詞彙