文件名称：论文：深度学习论文摘要
文件大小：58KB
文件格式：ZIP
更新时间：2024-02-23 19:22:15
machine-learning deep-neural-networks computer-vision deep-learning artificial-intelligence
论文：深度学习论文摘要
【文件预览】：
papers-master
----.gitignore(10B)
----README.md(13KB)
----reviews()
--------densecap-fully-convolutional-localization-networks-for-dense-captioning.md(2KB)
--------network-in-network.md(1KB)
--------delving-deeper-into-convolutional-networks-for-learning-video-representations.md(2KB)
--------neural-machine-translation-by-jointly-learning-to-align-and-translate.md(2KB)
--------a-simple-neural-network-module-for-relational-reasoning.md(3KB)
--------recurrent-batch-normalization.md(1KB)
--------learning-deep-features-for-scene-recognition-using-places-database.md(2KB)
--------towards-diverse-and-natural-image-descriptions-via-a-conditional-gan.md(2KB)
--------dynamic-capacity-networks.md(2KB)
--------deep-compositional-question-answering-with-neural-module-networks.md(3KB)
--------spatial-transformer-networks.md(2KB)
--------intriguing-properties-of-neural-networks.md(2KB)
--------sequence-to-sequence-learning-with-neural-networks.md(2KB)
--------deep-visual-analogy-making.md(2KB)
--------imagenet-classification-with-deep-convolutional-neural-networks.md(2KB)
--------actions-~-transformations.md(3KB)
--------how-transferable-are-features-in-deep-neural-networks.md(2KB)
--------from-red-wine-to-red-tomato-composition-with-context.md(832B)
--------neural-turing-machines.md(2KB)
--------deep-reinforcement-learning-for-dialogue-generation.md(3KB)
--------residual-networks-are-exponential-ensembles-of-relatively-shallow-networks.md(2KB)
--------are-you-talking-to-me-reasoned-visual-dialog-generation-through-adversarial-learning.md(2KB)
--------net2net-accelerating-learning-via-knowledge-transfer.md(2KB)
--------you-only-look-once-unified-real-time-object-detection.md(1KB)
--------identity-mappings-in-deep-residual-networks.md(4KB)
--------going-deeper-with-convolutions.md(2KB)
--------stacked-attention-networks-for-image-question-answering.md(3KB)
--------residual-networks-of-residual-networks-multilevel-residual-networks.md(1KB)
--------very-deep-convolutional-networks-for-large-scale-image-recognition.md(3KB)
--------draw-a-recurrent-neural-network-for-image-generation.md(1KB)
--------all-convolutional-net.md(2KB)
--------perceptual-losses-for-real-time-style-transfer-and-super-resolution.md(2KB)
--------object-detectors-emerge-in-deep-scene-cnns.md(3KB)
--------deep-networks-with-stochastic-depth.md(2KB)
--------what-question-would-turing-pose-today.md(2KB)
--------deep-inside-convolutional-networks.md(2KB)
--------rich-feature-hierarchies-for-accurate-object-detection-and-semantic-segmentation.md(2KB)
--------a-deep-compositional-framework-for-human-like-language-acquisition-in-virtual-environment.md(2KB)
--------building-machines-that-learn-and-think-like-people.md(2KB)
--------convolutional-neural-networks-for-sentence-classification.md(1KB)
--------visualizing-and-understanding-convolutional-networks.md(3KB)
--------deep-residual-learning-for-image-recognition.md(2KB)
--------world-models.md(2KB)