libs.garden
Most popular libraries and apps
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Deep Learning
mace — MACE is a deep learning inference framework o...
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MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms.
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XiaoMi/mace
v0.11.0-rc0
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Code for my publication: Deep Learning in Downlink Coordinated Multipoint in New Radio Heterogeneous Networks. Paper is under review.
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farismismar/DL-CoMP-Machine-Learning
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Predicting lncRNA-disease associations in heterogeneous network based on deep learning method.
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Pengeace/LncRNA-Disease-link
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Heterogeneous Run Time version of Caffe. Added heterogeneous capabilities to the Caffe, uses heterogeneous computing infrastructure framework to speed up Deep Learning on Arm-based heterogeneous embedded platform. It also retains all the features of the original Caffe architecture which users deploy their applications seamlessly.
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OAID/Caffe-HRT
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Motion flow and corresponding blurry image synthesis. Training data generation for "From Motion Blur to Motion Flow: A Deep Learning Solution for Removing Heterogeneous Motion Blur (CVPR'17)".
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donggong1/motion-flow-syn
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Heterogeneous Run Time version of TensorFlow. Added heterogeneous capabilities to the TensorFlow, uses heterogeneous computing infrastructure framework to speed up Deep Learning on Arm-based heterogeneous embedded platform. It also retains all the features of the original TensorFlow architecture which users deploy their applications seamlessly.
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OAID/TensorFlow-HRT
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Heterogeneous Run Time version of MXNet. Added heterogeneous capabilities to the MXNet, uses heterogeneous computing infrastructure framework to speed up Deep Learning on Arm-based heterogeneous embedded platform. It also retains all the features of the original MXNet architecture which users deploy their applications seamlessly.
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OAID/MXNet-HRT
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Deep Learning applications for NVIDIA DRIVE AGX platforms.
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NVIDIA/DL4AGX
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a web system to allow users to easily compose and execute full-stack Long Short Term Memory (LSTM) Recurrent Neural Network (RNN) workflows in web browsers by taking advantage of the online spatial data facilities, high-performance computation platforms, and open-source deep learning libraries.
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ESIPFed/Geoweaver
v0.7.0
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CaffePresso: An Optimized Library for Deep Learning on Embedded Accelerator-based platforms
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gplhegde/caffepresso
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We're team of technical geeks with passion in building apps, data and web services on all platforms and we do Analytics using Data Science. We are mastered in Artificial Intelligence(AI), Machine Learning(ML), Deep Learning
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mounicmadiraju/dataasservices
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Content consists of Jupyter Notebook tutorials walking through deep learning Frameworks (MXNet, Gluon) to Platforms (SageMaker, DeepLens) for common CV use-cases
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aws-samples/aws-ml-vision-end2end
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Code for the paper 'Deep Learning for Detecting Cyberbullying Across Multiple Social Media Platforms', ECIR'18
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sweta20/Detecting-Cyberbullying-Across-SMPs
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focus on several existing deep learning platforms from the perspective of compiling tech, e.g. TensorFlow XLA
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lijiansong/deep-learning
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This repository contains the material for deploying deep learning models on mobile and embedded platforms
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imohitch/DeepLearningOnAndroid
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Benchmarking deep learning models for real-time object detection on various platforms
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JesperChristensen89/object_detection_benchmarking
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Deep Learning Models optimized for AWS
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aws-samples/deep-learning-models
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A pre-configured Azure Data Science Virtual Machine with CPU-optimized Deep Learning Frameworks.
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IntelAI/azure-applications
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Multi-GPU ODE solver optimized for Deep Learning
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Zymrael/torchSODE
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Python script to generate fake datasets optimized for testing machine learning/deep learning workflows
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minimaxir/ml-data-generator
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Utilities for Intel optimized Deep learning frameworks
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vdevaram/deep_learning_utilities_cpu
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This is the code for the paper titleed task merge and scheduling for deep learning applications in mobile edge computing
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Derfei/task-merging-and-scheduling-for-deep-learning-applications-in-mobile-edge-computing
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Caffe deep learning framework - optimized for Xeon Phi
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rohithj/Xeon-CafPhi
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Deep Optimized Neural Networks: A library that can be used by people new to deep learning, to build optimized neural networks
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sharan-amutharasu/DONN
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Ansible configuration for GPU optimized Deep Learning with TensorFlow on EC2.
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cpetersen/brainiac
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A collection of Deep Learning for Affective Computing
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suzana-ilic/Deep_Learning_Affective_Computing
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Master's Thesis about running Deep Learning algorithms in a Fog Computing architecture
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adelinmaubray/miun_fog
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Deep learning for scientific computing
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lululxvi/sciconet
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Data Intensive Computing, Machine Learning and Deep Learning, Data mining
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crakama/Large-Scale-Data-Science-and-Engineering
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Distributed Deep Learning-based Offloading for Mobile Edge Computing Networks
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revenol/DDLO
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