45,862 research outputs found
Rule Of Thumb: Deep derotation for improved fingertip detection
We investigate a novel global orientation regression approach for articulated
objects using a deep convolutional neural network. This is integrated with an
in-plane image derotation scheme, DeROT, to tackle the problem of per-frame
fingertip detection in depth images. The method reduces the complexity of
learning in the space of articulated poses which is demonstrated by using two
distinct state-of-the-art learning based hand pose estimation methods applied
to fingertip detection. Significant classification improvements are shown over
the baseline implementation. Our framework involves no tracking, kinematic
constraints or explicit prior model of the articulated object in hand. To
support our approach we also describe a new pipeline for high accuracy magnetic
annotation and labeling of objects imaged by a depth camera.Comment: To be published in proceedings of BMVC 201
Prediction of Metabolic Pathways Involvement in Prokaryotic UniProtKB Data by Association Rule Mining
The widening gap between known proteins and their functions has encouraged
the development of methods to automatically infer annotations. Automatic
functional annotation of proteins is expected to meet the conflicting
requirements of maximizing annotation coverage, while minimizing erroneous
functional assignments. This trade-off imposes a great challenge in designing
intelligent systems to tackle the problem of automatic protein annotation. In
this work, we present a system that utilizes rule mining techniques to predict
metabolic pathways in prokaryotes. The resulting knowledge represents
predictive models that assign pathway involvement to UniProtKB entries. We
carried out an evaluation study of our system performance using
cross-validation technique. We found that it achieved very promising results in
pathway identification with an F1-measure of 0.982 and an AUC of 0.987. Our
prediction models were then successfully applied to 6.2 million
UniProtKB/TrEMBL reference proteome entries of prokaryotes. As a result,
663,724 entries were covered, where 436,510 of them lacked any previous pathway
annotations
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