… This work is an extended version of DeepCap [1] where additional explanations,
evaluations, comparisons, applications, and limitations are provided. In particular, the character …

… To this end, in this paper, we propose DeepCaps: a deep capsule network architecture
by leveraging two key ideas: Dynamic routing and Going deeper in the network. The novel …

… We propose a novel deep learning approach for monocular dense human performance
capture. Our method is trained in a weakly supervised manner based on multi-view supervision …

… The increased throughput of sequencers enables CAGE sequencing at a much deeper
scale than previously possible. On the one hand, this implies that it is increasingly possible to …

… The accuracies of these networNs at captioning though not comparable to humans yet but
comes out pretty high if trained effectively. The deep learning results for captioning help in …

… DeepCaps also introduce a skip connection between the last CapsCells to mitigate the
vanishing gradient effects that affect deeper … accuracy compared to DeepCaps-like structures, …

… DeepCAGE can produce much deeper transcriptome datasets and can reveal more details
… 1 μL of tRNA (20 μg) into the column and keep at room temperature for 1 min (see Note 15). …

… In this study, we proposed a deep learning model, DeepCap-Kcr, a capsule network (CapsNet)
based on a convolutional neural network (CNN) and long short-term memory (LSTM) for …

We present high-resolution sulfur and carbon isotope records from the cap carbonate of the
Doushantuo Formation, South China, a unique suite of depositional facies spanning across …

… This study proposes an analysis methodology for deep cap beams retrofitted with
externally bonded FRP fabrics. The methodology is presented in two stages with respective …