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In this paper we introduce a sparse kernel learning framework for the Continuous Relevance Model (CRM). State-of-the-art image annotation models linearly combine evidence from several different feature types to improve image annotation accuracy. While previous authors have focused on learning the linear combination weights for these features, there has been(More)
In this paper, we introduce a new form of the continuous relevance model (CRM), dubbed the SKL-CRM, that adaptively selects the best performing kernel per feature type for automatic image annotation. Previous image annotation models apply a standard selection of kernels to model the distribution of image features. Popular examples include a Gaussian kernel(More)
We introduce ReDites, a system for real-time event detection, tracking, monitoring and visualisation. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. Events are automatically detected from the Twitter stream. Then those that are categorised as being security-relevant are tracked,(More)
Androcam replaces calmodulin as a tissue-specific myosin VI light chain on the actin cones that mediate D. melanogaster spermatid individualization. We show that the androcam structure and its binding to the myosin VI structural (Insert 2) and regulatory (IQ) light chain sites are distinct from those of calmodulin and provide a basis for specialized myosin(More)
In this paper we propose Regularised Cross-Modal Hashing (RCMH) a new cross-modal hashing model that projects annotation and visual feature descriptors into a common Hamming space. RCMH optimises the hashcode similarity of related data-points in the annotation modality using an iterative three-step hashing algorithm: in the first step each training image is(More)
The degree to which behaviour, vertical movement and horizontal transport, in relation to local hydrodynamics, may facilitate secondary dispersal in the water column was studied in post-larval Sillaginodes punctata in Port Phillip Bay, Australia. S. punctata were captured in shallow seagrass beds and released at the surface in three depth zones (1.5, 3 and(More)
In this paper we show how word embeddings can be used to increase the effectiveness of a state-of-the art Locality Sensitive Hashing (LSH) based first story detection (FSD) system over a standard tweet corpus. Vocabulary mismatch, in which related tweets use different words, is a serious hindrance to the effectiveness of a modern FSD system. In this case, a(More)