… for information processing in our brain using a complex network of … When we fail to understand
the contents of an image … string allintitle: retrieval “cross modal” OR “cross media” OR “…

… not seem to be optimized. In particular, the authors aimed to better preserve the cross-language …
are used to train a Convolutional Neural Network for question answering task. Another …

… on (multimedia) information retrieval and multimedia signal … media has been shifted from
user-centric social networks (SN), … a unified optimization process, named unified visual contents …

… information fusion strategies in content-based image retrieval. Deep convolutional networks
… as a layer into deep networks, so that hash codes can be trained and optimized with deep …

… best of our knowledge, no work has been reported where tweet text and images are used
together to filter informative tweets from massive social media contents. … information extraction …

… a textual query or captions that precisely describe the content of a visual query. However,
solving … We can observe that by optimizing the loss function defined in (21), our SMAN model is …

… best of both worlds towards improved and more efficient cross-modal search and retrieval:
1) efficiency and simplicity of BE approaches based on twin networks, as well as 2) …

… guidelines (rules) that might be useful for authors and reviewers. As benchmarking in optimization
… content of most sections should be applicable. Each of the following sections presents …

… Initially, an interactive optimization model is applied to … data gives semantic cues regarding
image contents, it is not … server, and software defined network, which utilizes virtualization …

… understand not only the content of images and texts but also … from the Internet and optimized
the retrieval model with them. … Memory network (IMRAM) for cross-modal image-text retrieval …