GitHub topics: resource-constrained-ml
microsoft/EdgeML
This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.
Language: C++ - Size: 78.5 MB - Last synced at: about 19 hours ago - Pushed at: about 1 year ago - Stars: 1,617 - Forks: 375
zeyneddinoz/subMFL
subMFL: Compatible subModel Generation for Federated Learning in Device Heterogeneous Environment
Language: Jupyter Notebook - Size: 125 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 2 - Forks: 1
Ekhao/DataAwareNeuralArchitectureSearch
A proof of concept implementation of a Data Aware Neural Architecture Search.
Language: Python - Size: 336 KB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 3 - Forks: 1
nandahkrishna/StressAffectDetection
Code for Stress and Affect Detection on Resource-Constrained Devices
Language: Jupyter Notebook - Size: 389 KB - Last synced at: about 1 month ago - Pushed at: over 4 years ago - Stars: 12 - Forks: 8
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
Language: Jupyter Notebook - Size: 27.7 MB - Last synced at: over 1 year ago - Pushed at: about 3 years ago - Stars: 0 - Forks: 1
wesamnabeel99/neural-network-compression
Image classification using compressed deep neural network ported on resource-constrained platforms.
Language: Python - Size: 89.8 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0
vishaln15/OptimizedArrhythmiaDetection
Code for Optimized Arrhythmia Detection on Ultra-Edge Devices
Language: Jupyter Notebook - Size: 461 KB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 4 - Forks: 4
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)
Language: Python - Size: 52.3 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 3 - Forks: 1
tanveer-hussain/Embedded-Vision-for-MVS
Embedded Vision for MVS in IoT
Language: Python - Size: 86.9 KB - Last synced at: about 2 years ago - Pushed at: almost 4 years ago - Stars: 6 - Forks: 3
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)
Language: Python - Size: 514 KB - Last synced at: almost 2 years ago - Pushed at: almost 4 years ago - Stars: 9 - Forks: 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
Language: Python - Size: 16.2 MB - Last synced at: almost 2 years ago - Pushed at: about 6 years ago - Stars: 0 - Forks: 0