Ai-benchmark.com

Ai-benchmark.com has Server used 192.30.252.154 IP Address with Hostname in United States. Below listing website ranking, Similar Webs, Backlinks. This domain was first 2018-04-26 (1 year, 179 days) and hosted in San Francisco United States, server ping response time 11 ms

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Website: Ai-benchmark.com
Hostname: lb-192-30-252-154-iad.github.com
Country:
Region: CA
City: San Francisco
Postal Code: 94107
Latitude: 37.76969909668
Longitude: -122.39330291748
Area Code: 415
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Found 56 Websites with content related to this domain, It is result after search with search engine

AI-Benchmark

Is your smartphone capable of running the latest Deep Neural Networks to perform these AI-based tasks? Is it fast enough? Run AI Benchmark to test several key AI tasks on your phone and check its performance!

http://ai-benchmark.com/

AI Benchmark - Apps on Google Play

Face Recognition, Image Classification, Image Enhancement Is your smartphone capable of running the latest Deep Neural Networks to perform these AI-based tasks?

https://play.google.com/store/apps/details?id=org.benchmark.demo&hl=en_US

AI Benchmark – Aplikace na Google Play

Face Recognition, Image Classification, Image Enhancement Is your smartphone capable of running the latest Deep Neural Networks to perform these AI-based tasks?

https://play.google.com/store/apps/details?id=org.benchmark.demo&hl=cs

Baidu Releases AI Benchmark | EE Times

Baidu Releases AI Benchmark Intel, Nvidia post results training neural nets . By Rick Merritt, 09.26.16 2. Share Post. Share on Facebook. Share on Twitter. SAN JOSE, Calif. – Calling for 100x faster processors, China Web giant Baidu released DeepBench, an open source benchmark for how fast processors train neural networks for machine learning.

https://www.eetimes.com/document.asp?doc_id=1330521

AI Benchmark: Running Deep Neural Networks on Android

this paper, we present an AI Benchmark designed specifically to test the machine learning performance, available hardware AI accelerators, chipset drivers, and memory limitations of the current Android devices. It consists of a number of computer vision AI tests that are executed directly on the phones’ hard-

https://arxiv.org/pdf/1810.01109.pdf

ML-Bench 1.0 Constructing and Analyzing a Machine-Learning

ML-Bench 1.0 Constructing and Analyzing a Machine-Learning Benchmark. September 16, 2016. Overview; Translating This is a computer translation of the original content. It is provided for general information only and should not be relied upon as complete or accurate.

https://software.intel.com/en-us/videos/l-bench-10-constructing-and-analyzing-a-machine-learning-benchmark

Stanford DAWN Deep Learning Benchmark (DAWNBench)

DAWNBench is a benchmark suite for end-to-end deep learning training and inference. Computation time and cost are critical resources in building deep models, yet many existing benchmarks focus solely on model accuracy.

https://dawn.cs.stanford.edu/benchmark/

Benchmarks.AI - Directory of AI Benchmarks

Benchmark Description; MNIST: Classify handwritten digits. CIFAR-10: Classify 32x32 colour images into 10 categories. CIFAR-100: Classify 32x32 colour images into 100 categories.

https://benchmarks.ai/

CIFAR-100 on Benchmarks.AI

GPipe is a scalable pipeline parallelism library that enables learning of giant deep neural networks. It partitions network layers across accelerators and pipelines execution to achieve high hardware utilization.

https://benchmarks.ai/cifar-100

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