resource-constrained-ml

There are 2 repositories under resource-constrained-ml topic.

microsoft / EdgeML
This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.
iot-device sensor edge-machine-learning resource-constrained-ml machine-learning-algorithms microsoft-research machine-learning tensorflow deep-learning edge-computing microsoft edge-devices classifier emi-rnn pytorch bonsai protonn fastgrnn cpp fastrnn
Language:C++ 1534
nandahkrishna / StressAffectDetection
Code for Stress and Affect Detection on Resource-Constrained Devices
machine-learning stress stress-detection affect affect-recognition affective-computing efficient resource-constrained-ml state-of-the-art research raspberry-pi-3 sensor-data real-time time-series deep-learning
Language:Jupyter Notebook 10
radu-dogaru / ELM-super-fast
Python implementation of ELM - with optimized speed on MKL-based platforms; Described in conference paper: Radu Dogaru, Ioana Dogaru, "Optimization of extreme learning machines for big data applications using Python", COMM-2018; Allows quantization of weight parameters in both layers and introduces a new and very effective hidden layer nonlinearity (absolute value)
extreme-learning-machine resource-constrained-ml
Language:Python 9
vishaln15 / OptimizedArrhythmiaDetection
Code for Optimized Arrhythmia Detection on Ultra-Edge Devices
research raspberry-pi-3b resource-constrained-ml machine-learning bonsai efficient optimized atrial-fibrillation-detection arrhythmia-detection
Language:Jupyter Notebook 8
tanveer-hussain / Embedded-Vision-for-MVS
Embedded Vision for MVS in IoT
embedded-vision raspberry-pi-3 resource-constrained-ml summarization-framework video video-analysis video-summaries video-summarization
Language:Python 7
bmanczak / BEP
This repository is devoted to the development of the facial emotion recognition (FER) system as a final bachelor project at the TU/e. Realised by Blazej Manczak. Supervisors: Dr. Laura Astola (Accenture) and Dr. Vlado Menkovski (TU/e)
facial-emotion-recognition affectnet fer raf-db resource-constrained-ml
Language:Python 4
Ekhao / DataAwareNeuralArchitectureSearch
A proof of concept implementation of a Data Aware Neural Architecture Search.
neural-architecture-search neural-networks resource-constrained-ml tinyml
Language:Python 1
zeyneddinoz / subMFL
subMFL: Compatible subModel Generation for Federated Learning in Device Heterogeneous Environment
decentralized-learning distributed-learning edge-computing edge-intelligence federated-learning heterogeneous-environment mobile-edge-agent model-compression model-generalization model-personalization model-pruning ondeviceai resource-constrained-devices resource-constrained-ml statistical-heterogeneity trustworthy-ai
Language:Jupyter Notebook 1
radu-dogaru / NL-CNN-RDT-based-sound-classification-
Models and their evaluation for paper: Radu Dogaru and Ioana Dogaru "RD-CNN: A Compact and Efficient Convolutional Neural Net for Sound Classification ", ISETC-2020
sound-recognition convolutional-neural-networks resource-constrained-ml
Language:Jupyter Notebook 0
radu-dogaru / Super_Fast_Vector_Classifier
A Python implementation of the algorithm described in paper Radu Dogaru, Ioana Dogaru, "Optimized Super Fast Support Vector Classifiers Using Python and Acceleration of RBF Computations", (2018) ; There is no output layer learning only a relatively fast selection of support vectors in a RBF-layer optimized for speed. Faster than SVM
resource-constrained-ml support-vector-machines classification-algorithm
Language:Python

resource-constrained-ml

microsoft / EdgeML

nandahkrishna / StressAffectDetection

radu-dogaru / ELM-super-fast

vishaln15 / OptimizedArrhythmiaDetection

tanveer-hussain / Embedded-Vision-for-MVS

bmanczak / BEP

Ekhao / DataAwareNeuralArchitectureSearch

zeyneddinoz / subMFL

radu-dogaru / NL-CNN-RDT-based-sound-classification-

radu-dogaru / Super_Fast_Vector_Classifier