Image Representations and New Domains inNeural Image Captioning
we find that a state-of-theart neuralcaptioning algorithm is able to produce quality captions even when providedwith surprisingly poor image representations
Deep Boosting: Joint Feature Selection andAnalysis Dictionary Learning in Hierarchy
This work investigates how the traditionalimage classification pipelines can be extended into a deep architecture,inspired by recent successes of deep neural networks
Digging Deep into the layers of CNNs: InSearch of How CNNs Achieve View Invariance
A practical guide to CNNs and FisherVectors for image instance retrieval
CNN robust to scale but not robust torotation (unless your training data contains rotation samples)
FV + CNN maybe better
Submodular Reranking with Multiple FeatureModalities for Image Retrieval
Our submodularreranking framework can be easily generalized to any generic reranking problemsfor real-time search engines
Benchmarking of LSTM Networks

本文深入探讨了深度学习领域的最新进展,包括图像代表性和新领域中的神经图像描述,如图像分类管道的深度架构扩展、CNN的层次分析、CNN在图像检索中的应用及增强方法,以及子模态相关排名在图像检索中的应用。
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