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related paper
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|In this work we investigate **the effect of the convolutional network depth** on its accuracy in the large-scale image recognition setting. Our main contribution is a th…
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There has been current work going on with ABM Edge large scale rollout [here](https://github.com/GoogleCloudPlatform/anthos-edge-usecases). One of the common workloads we've been seeing on the Edge is…
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Suyog Gupta, Ankur Agrawal, Kailash Gopalakrishnan, Pritish Narayanan
Training of large-scale deep neural networks is often constrained by the available computational resources. We study the effect…
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thanks for this great job. your paper just report the minist\cifar scores. do you have train model for imagenet or other largescale dataset? can you share more experience for this largescale image …
zjupx updated
5 years ago
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I've been working on a similar idea for a while and then stumbled upon this via another project I've been following.
While the method works (images deemed inappropriate get blurred and the tag work…
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https://doi.org/10.1093/bioinformatics/btx680
>MOTIVATION:
Annotation of enzyme function has a broad range of applications, such as metagenomics, industrial biotechnology, and diagnosis of enzyme …
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Hi,
I have a multivariate classification problem where I'm trying to classify an uneven length time series, but zero padding would not work well for me since the difference between the smallest and…
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Per the log, it uses a ResNet101 model with a batch-size of 128 (per GPU).
This causes out-of-memory on at least two flavors of GPU drivers (ROCm and CUDA) w/16GB GPU memory.
`RuntimeError: CU…
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Hey, I'm trying to get the modivius chip to recognize objects in a 1920x080 image. My current understanding is that the modivius chip will downscale the image to 256x256 (or 160x160) because of the im…
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### Project Name:
Apply Random Quantum Neural Network on Noisy Medical Image Recognition
### Team Name: QIAO
### Which challenges would you like to submit your project for?
- Hybrid Quantum-Cla…