Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN)

In this paper, we present a multimodal Recurrent Neural Network (m-RNN) model for generating novel image captions. It directly models the probability distribution of generating a word given previous words and an image. Image captions are generated by sampling from this distribution. The model consists of two sub-networks: a deep recurrent neural network for sentences and a deep convolutional network for images. These two sub-networks interact with each other in a multimodal layer to form the whole m-RNN model. The effectiveness of our model is validated on four benchmark datasets (IAPR TC-12, Flickr 8K, Flickr 30K and MS COCO). Our model outperforms the state-of-the-art methods. In addition, we apply the m-RNN model to retrieval tasks for retrieving images or sentences, and achieves significant performance improvement over the state-of-the-art methods which directly optimize the ranking objective function for retrieval. The project page of this work is: www.stat.ucla.edu/~junhua.mao/m-RNN.html .Comment: Add a simple strategy to boost the performance of image captioning task significantly. More details are shown in Section 8 of the paper. The code and related data are available at https://github.com/mjhucla/mRNN-CR ;. arXiv admin note: substantial text overlap with arXiv:1410.109

Method of location estimating for a vehicle by using image processing

金沢大学工学部A method was proposed for finding the position and direction of vehicles by processing the images of flat landmarks. For multiple landmarks set in a wide area, the vehicle can run in an arbitrary space. Since a low locating accuracy was found at the right frontal area of the flat landmark, a cubic landmark is proposed here to improve the locating accuracy, and the experimental result is reported here

Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN)

In this paper, we present a multimodal Recurrent Neural Network (m-RNN) model for generating novel image captions. It directly models the probability distribution of generating a word given previous words and an image. Image captions are generated according to this distribution. The model consists of two sub-networks: a deep recurrent neural network for sentences and a deep convolutional network for images. These two sub-networks interact with each other in a multimodal layer to form the whole m-RNN model. The effectiveness of our model is validated on four benchmark datasets (IAPR TC-12, Flickr 8K, Flickr 30K and MS COCO). Our model outperforms the state-of-the-art methods. In addition, the m-RNN model can be applied to retrieval tasks for retrieving images or sentences, and achieves significant performance improvement over the state-of-the-art methods which directly optimize the ranking objective function for retrieval.This work was supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF - 1231216

Tetragonal Mexican-Hat Dispersion and Switchable Half-Metal State with Multiple Anisotropic Weyl Fermions in Penta-Graphene

In past decades, the ever-expanding library of 2D carbon allotropes has yielded a broad range of exotic properties for the future carbon-based electronics. However, the known allotropes are all intrinsic nonmagnetic due to the paired valence electrons configuration. Based on the reported 2D carbon structure database and first-principles calculations, herein we demonstrate that inherent ferromagnetism can be obtained in the prominent allotrope, penta-graphene, which has an unique Mexican-hat valence band edge, giving rise to van Hove singularities and electronic instability. Induced by modest hole-doping, being achievable in electrolyte gate, the semiconducting pentagraphene can transform into different ferromagnetic half-metals with room temperature stability and switchable spin directions. In particular, multiple anisotropic Weyl states, including type-I and type-II Weyl cones and hybrid quasi Weyl nodal loop, can be found in a sizable energy window of spin-down half-metal under proper strains. These findings not only identify a promising carbon allotrope to obtain the inherent magnetism for carbon-based spintronic devices, but highlight the possibility to realize different Weyl states by combining the electronic and mechanical means as well

PI3Ks Maintain the Structural Integrity of T-Tubules in Cardiac Myocytes

Phosphoinositide 3-kinases (PI3Ks) regulate numerous physiological processes including some aspects of cardiac function. Although regulation of cardiac contraction by individual PI3K isoforms has been studied, little is known about the cardiac consequences of downregulating multiple PI3Ks concurrently.Genetic ablation of both p110α and p110β in cardiac myocytes throughout development or in adult mice caused heart failure and death. Ventricular myocytes from double knockout animals showed transverse tubule (T-tubule) loss and disorganization, misalignment of L-type Ca(2+) channels in the T-tubules with ryanodine receptors in the sarcoplasmic reticulum, and reduced Ca(2+) transients and contractility. Junctophilin-2, which is thought to tether T-tubules to the sarcoplasmic reticulum, was mislocalized in the double PI3K-null myocytes without a change in expression level.PI3K p110α and p110β are required to maintain the organized network of T-tubules that is vital for efficient Ca(2+)-induced Ca(2+) release and ventricular contraction. PI3Ks maintain T-tubule organization by regulating junctophilin-2 localization. These results could have important medical implications because several PI3K inhibitors that target both isoforms are being used to treat cancer patients in clinical trials

Méthodologie moderne de la détermination du géoïde

Modern methodology for geoid determination use for the production of an operational vertical referenceL’accroissement des données disponibles, grâce aux techniques spatiales, ainsi que le développement de nouvelles méthodes mathématiques pour traiter ces données, permettent aujourd'hui de calculer un géoïde gravimétrique d'une précision de l'ordre de quelques centimètres. A l'heure actuelle, la détermination du géoïde est basée sur la combinaison de données terrestres et de données spatiales en introduisant un modèle global de géopotentiel comme référence. De nouvelles techniques, telles que la collocation, l'intégration rapide, l'ajustement combiné ou la combinaison optimale, facilitent et accélèrent l'obtention d'un géoïde précis. Les calculs de géoïde en France ainsi qu'en Belgique illustrent le bénéfice, aussi bien en précision qu'en temps de calcul, apporte par ces nouvelles méthodes

Concept Lattice Method for Spatial Association Discovery in the Urban Service Industry

A relative lag in research methods, technical means and research paradigms has restricted the rapid development of geography and urban computing. Hence, there is a certain gap between urban data and industry applications. In this paper, a spatial association discovery framework for the urban service industry based on a concept lattice is proposed. First, location data are used to form the formal context expressed by 0 and 1. Frequent closed itemsets and a concept lattice are computed on the basis of the formal context of the urban service industry. Frequent closed itemsets can filter out redundant information in frequent itemsets, uniquely determine the complete set of all frequent itemsets, and be orders of magnitude smaller than the latter. Second, spatial frequent closed itemsets and association rules discovery algorithms are designed and built based on the formal context. The inputs of the frequent closed itemsets discovery algorithms include the given formal context and frequent threshold value, while the outputs are all frequent closed itemsets and the partial order relationship between them. Newly added attributes create new concepts to guarantee the uniqueness of the new spatial association concept. The inputs of spatial association rules discovery algorithms include frequent closed itemsets and confidence threshold values, and a rule is confident when and only if its confidence degree is not less than the confidence threshold value. Third, the spatial association of the urban service industry in Nanning, China is taken as a case to verify the method. The results are basically consistent with the spatial distribution of the urban service industry in Nanning City. This study enriches the theories and methods of geography as well as urban computing, and these findings can provide guidance for location-based service planning and management of urban services