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This paper presents a novel approach for automatically generating image descriptions: visual detectors, language models, and multimodal similarity models learnt directly from a dataset of image captions. We use multiple instance learning to train visual detectors for words that commonly occur in captions, including many different parts of speech such as(More)
In this paper we describe the Microsoft COCO Caption dataset and evaluation server. When completed, the dataset will contain over one and a half million captions describing over 330,000 images. For the training and validation images, five independent human generated captions will be provided. To ensure consistency in evaluation of automatic caption(More)
Two recent approaches have achieved state-of-the-art results in image captioning. The first uses a pipelined process where a set of candidate words is generated by a convolutional neural network (CNN) trained on images, and then a maximum entropy (ME) language model is used to arrange these words into a coherent sentence. The second uses the penultimate(More)
In automatic guidance of agriculture vehicles, lateral control is not the only requirement. Lots of research works have been focused on trajectory tracking control which can provide high longitudinal-lateral control accuracy. Satisfactory results have been reported as soon as vehicles move without sliding. But unfortunately pure rolling constraints are not(More)
We develop a novel bi-directional attention model for dependency parsing, which learns to agree on headword predictions from the forward and backward parsing directions. The parsing procedure for each direction is formulated as sequentially querying the memory component that stores continuous headword embeddings. The proposed parser makes use of soft(More)
Peritoneal macrophages (PMs) from toll-like receptor 4 (TLR4)-deficient and wild-type (WT) mice were responsive to recombinant Toxoplasma gondii-derived heat shock protein 70 (rTgHSP70) and natural TgHSP70 (nTgHSP70) in NO release, but those from TLR2-, myeloid differentiation factor 88 (MyD88)-, and interleukin-1R-associated kinase 4 (IRAK4)-deficient mice(More)
This paper develops a new method to solve multivariate discrete-continuous problems and applies the model to measure the influence of residential density on households’ vehicle fuel efficiency and usage choices. Traditional discrete-continuous modelling of vehicle holding choice and vehicle usage becomes unwieldy with large numbers of vehicles and vehicle(More)
BACKGROUND/AIMS although numerous studies have explored the mechanisms regulating the enzyme activity of NADPH oxidase in diabetic nephropathy (DN), little information is available for the contribution of microRNAs (miRNAs) to the regulation of NADPH oxidase expression. Therefore, the present study was to test whether miRNAs importantly contribute to the(More)
Differential evolution (DE) and particle swarm optimization (PSO) are two formidable population-based optimizers (POs) that follow different philosophies and paradigms, which are successfully and widely applied in scientific and engineering research. The hybridization between DE and PSO represents a promising way to create more powerful optimizers,(More)
Traditional compressed sensing considers sampling a 1D signal. For a multidimensional signal, if reshaped into a vector, the required size of the sensing matrix becomes dramatically large, which increases the storage and computational complexity significantly. To solve this problem, the multidimensional signal is reshaped into a 2D signal, which is then(More)