Dynamic gating in multi-modular neural networks using random connectionsBurak, YoramRIGOTTI, MFusi, S
As shown in Fig.3, X is mapped to the feature map U through any given transformation, such as convolution. For the feature U, we first make a feature descriptor by a squeezing operation. Then an excitation operation is followed, which uses a simple self-gating mechanism, takes feature desc...
To realize molecular-scale electrical operations beyond the von Neumann bottleneck, new types of multifunctional switches are needed that mimic self-learning or neuromorphic computing by dynamically toggling between multiple operations that depend on the
FIG.6illustrates an example of an implementation of head tracking or other device tracking using a game controller having a DVS with dual sensor arrays according to an aspect of the present disclosure. Here the controller605is coupled to two DVS606,607or a single DVS having two light sensitive...
This paper surveys variational approaches for image reconstruction in dynamic inverse problems. Emphasis is on variational methods that rely on parametrized temporal models. These are encoded here as diffeomorphic deformations with time-dependent paramet
Channel and layer gatingCNNResNetImage classificationConvolutional neural networks (CNN) are getting more and more complex, needing enormous computing resources and energy. In this paper, we propose methods for conditional computation in the context of image classification that allows a CNN to ...
An example of the standard gating strategy for flow cytometry analysis. Cells are gated based on side scatter (SSC) and forward scatter (FSC). Single cells are then gated based on FSC-width (W) vs FSC-height (H) followed by gating live cells based on DAPI exclusion. Single, viable cells...
Neural mechanisms of dual-task interference and cognitive capacity limitation in the prefrontal cortex. Nat. Neurosci. 17, 601–611 (2014). CAS PubMed Google Scholar Watanabe, K. & Funahashi, S. Prefrontal delay-period activity reflects the decision process of a saccade direction during a free...
The proposed SelfCoLearn is equipped with three important components, namely, dual-network collaborative learning, reunderampling data augmentation and a special-designed co-training loss. The framework is flexible and can be integrated into various model-based iterative un-rolled networks. The ...
To address the issue of low accuracy in the segmentation of dynamic objects using semantic segmentation networks, a dual-branch dynamic object segmentation network has been proposed, which is based on the fusion of spatiotemporal information. First, an a