discriminators matter
区分器很重要
using discriminators
使用区分器
discriminator design
区分器设计
discriminators identified
已识别的区分器
complex discriminators
复杂的区分器
discriminator features
区分器特征
trained discriminators
训练过的区分器
discriminator performance
区分器性能
discriminators improved
改进的区分器
good discriminators
好的区分器
the ai model used discriminators to distinguish between real and fake images.
人工智能模型使用判别器来区分真实图像和虚假图像。
we trained the neural network with multiple discriminators for improved performance.
我们使用多个判别器训练神经网络，以提高性能。
the discriminator's role is to evaluate the generator's output in gans.
判别器的作用是在生成对抗网络中评估生成器的输出。
adversarial training involves a generator and a discriminator competing against each other.
对抗训练涉及生成器和判别器相互竞争。
the discriminator provided valuable feedback to the generator during training.
判别器在训练过程中为生成器提供了有价值的反馈。
we compared the performance of different discriminator architectures.
我们比较了不同判别器架构的性能。
the discriminator learned to identify subtle differences in the data.
判别器学会了识别数据中的细微差别。
a well-designed discriminator is crucial for successful gan training.
精心设计的判别器对于成功的生成对抗网络训练至关重要。
the discriminator's loss function guided the generator's learning process.
判别器的损失函数指导了生成器的学习过程。
we used a convolutional discriminator for image generation tasks.
我们使用卷积判别器进行图像生成任务。
the discriminator's accuracy improved as the training progressed.
随着训练的进行，判别器的准确性提高了。
discriminators matter
区分器很重要
using discriminators
使用区分器
discriminator design
区分器设计
discriminators identified
已识别的区分器
complex discriminators
复杂的区分器
discriminator features
区分器特征
trained discriminators
训练过的区分器
discriminator performance
区分器性能
discriminators improved
改进的区分器
good discriminators
好的区分器
the ai model used discriminators to distinguish between real and fake images.
人工智能模型使用判别器来区分真实图像和虚假图像。
we trained the neural network with multiple discriminators for improved performance.
我们使用多个判别器训练神经网络，以提高性能。
the discriminator's role is to evaluate the generator's output in gans.
判别器的作用是在生成对抗网络中评估生成器的输出。
adversarial training involves a generator and a discriminator competing against each other.
对抗训练涉及生成器和判别器相互竞争。
the discriminator provided valuable feedback to the generator during training.
判别器在训练过程中为生成器提供了有价值的反馈。
we compared the performance of different discriminator architectures.
我们比较了不同判别器架构的性能。
the discriminator learned to identify subtle differences in the data.
判别器学会了识别数据中的细微差别。
a well-designed discriminator is crucial for successful gan training.
精心设计的判别器对于成功的生成对抗网络训练至关重要。
the discriminator's loss function guided the generator's learning process.
判别器的损失函数指导了生成器的学习过程。
we used a convolutional discriminator for image generation tasks.
我们使用卷积判别器进行图像生成任务。
the discriminator's accuracy improved as the training progressed.
随着训练的进行，判别器的准确性提高了。
探索常用高频词汇