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IamNN: Iterative and Adaptive Mobile Neural Network for Efficient Image Classification
[article]
2018
arXiv
pre-print
Preserved Fulltext
The resulting network is much smaller than the original network and can adapt the computational cost to the complexity of the input image. ...
In this work we use these properties to design a network based on a ResNet but with parameter sharing and with adaptive computation time. ...
We combined these two ideas of parameter sharing and adaptive computation time to design a building block for accurate deep neural networks with small model size and adaptive computational cost. ...
arXiv:1804.10123v1
fatcat:vkls76zzmjar3mfmufnxo53epi
Dynamic Neural Networks: A Survey
[article]
2021
arXiv
pre-print
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
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2021 pre-print arXiv:2102.04906v2 fatcat:rqjjjsavdrglbmlujtc6x4t7vqOther Versions
adaptive inference along the temporal dimension for sequential data such as videos and texts. ...
architectures or parameters; 2) spatial-wise dynamic networks that conduct adaptive computation with respect to different spatial locations of image data and 3) temporal-wise dynamic models that perform ...
Rather than skipping the execution of layers with independent parameters, iterative and adaptive mobile neural network (IamNN) [64] replaces multiple residual blocks in each ResNet stage by one block ...
arXiv:2102.04906v4
fatcat:zelspxwv6nel7kv2yu6ynakyuu
Goal-Driven Recurrent Neural Network Models of the Ventral Visual Stream
[article]
2021
bioRxiv
pre-print
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
We then compared these models to temporally fine-grained neural and behavioral recordings from primates to thousands of images. ...
We found that ConvRNNs better matched these data than alternative models, including the deepest feedforward networks, on two metrics: 1) neural dynamics in V4 and inferotemporal (IT) cortex at late timepoints ...
Iamnn: iterative and adaptive mobile neural network for efficient image
470
470
classification. ...
doi:10.1101/2021.02.17.431717
fatcat:pxxpa76365b7lcpxud7fygq5se