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Monocular Depth Estimation with Self-Supervised Learning for Vineyard Unmanned Agricultural Vehicle
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In: Sensors (Basel) (2022)
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Translational regulation of Chk1 expression by eIF3a via interaction with the RNA-binding protein HuR
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In: Biochem J (2020)
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Lexical richness of Chinese candidates in the graded oral English examinations
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Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking ...
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Additional file 1: of Estimating the prevalence of schistosomiasis japonica in China: a serological approach ...
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Additional file 1: of Estimating the prevalence of schistosomiasis japonica in China: a serological approach ...
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Alkali-silica reaction in waterglass-activated slag mortars incorporating fly ash and metakaolin
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Domain adaptation for statistical machine translation and neural machine translation
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Zhang, Jian. - : Dublin City University. School of Computing, 2017. : Dublin City University. ADAPT, 2017
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In: Zhang, Jian orcid:0000-0001-5659-5865 (2017) Domain adaptation for statistical machine translation and neural machine translation. PhD thesis, Dublin City University. (2017)
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Fast gated neural domain adaptation: language model as a case study
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In: Zhang, Jian orcid:0000-0001-5659-5865 , Wu, Xiaofeng, Way, Andy orcid:0000-0001-5736-5930 and Liu, Qun orcid:0000-0002-7000-1792 (2017) Fast gated neural domain adaptation: language model as a case study. In: Proceedings of FETLT 2016: Future and Emerging Trends in Language Technologies, Machine Learning and Big Data, 30 Nov- 2 Dec 2016, Seville, Spain. (2017)
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Refining Image Categorization by Exploiting Web Images and General Corpus ...
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Abstract:
Studies show that refining real-world categories into semantic subcategories contributes to better image modeling and classification. Previous image sub-categorization work relying on labeled images and WordNet's hierarchy is not only labor-intensive, but also restricted to classify images into NOUN subcategories. To tackle these problems, in this work, we exploit general corpus information to automatically select and subsequently classify web images into semantic rich (sub-)categories. The following two major challenges are well studied: 1) noise in the labels of subcategories derived from the general corpus; 2) noise in the labels of images retrieved from the web. Specifically, we first obtain the semantic refinement subcategories from the text perspective and remove the noise by the relevance-based approach. To suppress the search error induced noisy images, we then formulate image selection and classifier learning as a multi-class multi-instance learning problem and propose to solve the employed problem ...
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Keyword:
Computer Vision and Pattern Recognition cs.CV; FOS Computer and information sciences; Multimedia cs.MM
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URL: https://arxiv.org/abs/1703.05451 https://dx.doi.org/10.48550/arxiv.1703.05451
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The global view of mRNA-related ceRNA cross-talks across cardiovascular diseases
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Two-Stage Friend Recommendation Based on Network Alignment and Series Expansion of Probabilistic Topic Model
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In: Faculty of Engineering and Information Sciences - Papers: Part B (2017)
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Topic-informed neural machine translation
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In: Zhang, Jian, Li, Liangyou orcid:0000-0002-0279-003X , Way, Andy orcid:0000-0001-5736-5930 and Liu, Qun orcid:0000-0002-7000-1792 (2016) Topic-informed neural machine translation. In: 26th International Conference on Computational Linguistics, 13-16 Dec 2016, Osaka, Japan. (2016)
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Chinese Relative Clauses Processing in Supportive Context Removing Ambiguity
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In: Studies in Literature and Language; Vol 1, No 4 (2010): Studies in Literature and Language; 12-19 ; 1923-1563 ; 1923-1555 (2010)
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