In this paper, the optimum shape of Tailor-Welded Blanks (TWB) is investigated. The optimization is performed for two different case studies. The first example is deep drawing of a TWB with dissimilar materials and uniform thicknesses and the next example is deep drawing of a TWB with similar materials and non-uniform thicknesses. The effect of blank optimization on the weld line movement is...

Neuromorphic hardware tends to pose limits on the connectivity of deep networks that one can run on them. But also generic hardware and software implementations of deep learning run more efficiently on sparse networks. Several methods exist for pruning connections of a neural network after it was trained without connectivity constraints. We present an algorithm, DEEP R, that enables us to train...

We discuss problems with the standard approaches to evaluation for tasks like visual question answering, and argue that artificial data can be used to address these as a complement to current practice. We demonstrate that with the help of existing ‘deep’ linguistic processing technology we are able to create challenging abstract datasets, which enable us to investigate the language understandin...

Architectural efforts are exploring many dimensions for network backbones, designing deeper or wider architectures, but how to best aggregate layers and blocks across a network deserves further attention. We augment standard architectures with deeper aggregation to better fuse information across layers. Our deep layer aggregation structures iteratively and hierarchically merge the feature hiera...

Until now we have mostly studied the proposed approximate inference techniques empirically. In this chapter we turn to a more theoretical analysis, and concentrate mostly on the case of dropout, as it seems to be the most widely used among the various stochastic regularisation techniques. We begin by suggesting practical considerations for getting good uncertainty estimates, followed by a revie...

Convolutional Networks (ConvNets) have recently improved image recognition performance thanks to end-to-end learning of deep feed-forward models from raw pixels. Deep learning is a marked departure from the previous state of the art, the Fisher Vector (FV), which relied on gradient-based encoding of local hand-crafted features. In this paper, we discuss a novel connection between these two appr...

conclusion pharmacomechanical thrombectomy provides very satisfactory results in a single procedure, as a new method in the treatment of acute and subacute deep vein thrombosis. background in this study, we shared the implementation success and clinical results for 38 patients treated with the cleaner™ pharmacomechanical thrombectomy device. objectives the impact and results of pharmacomechanic...