Topic: fully-connected-deep-neural-network Goto Github
Some thing interesting about fully-connected-deep-neural-network
Some thing interesting about fully-connected-deep-neural-network
fully-connected-deep-neural-network,Neural Networks Classification on Fashion MNIST.
User: abuzariii
fully-connected-deep-neural-network,This projects constructs the fully connected layered (MLP)neural network models to predict the cardio vascular disease in the patient.To validate the models constructed, an ensemble method (using the voting) is implemented.
User: apurvakatti19
fully-connected-deep-neural-network,This repository contains various networks implementation such as MLP, Hopfield, Kohonen, ART, LVQ1, Genetic algorithms, Adaboost and fuzzy-system, CNN with python.
User: ghazaleh-mahmoodi
fully-connected-deep-neural-network,Explain fully connected ReLU neural networks using rules
User: groshanlal
fully-connected-deep-neural-network,BlessMark: A Blind Diagnostically-Lossless Watermarking Framework for Medical Applications Based on Deep Neural Networks
User: hamidrezazarrabi
fully-connected-deep-neural-network,Application of Fully Connected Neural Networks (FCNs) & Graphical Convolutional Neural Networks (GCNs) using pytorch to fmri movie data
User: hanmacrad2
fully-connected-deep-neural-network,CS 182 Spring 2019 - Assignment 1
User: nadernamini
fully-connected-deep-neural-network,MNIST handwritten digit classification using PyTorch
User: nvsyashwanth
fully-connected-deep-neural-network,My projects from the Udacity Deep Learning Nanodegree.
User: shubham-sk
fully-connected-deep-neural-network,Implemented fully-connected DNN of arbitrary depth with Batch Norm and Dropout, three-layer ConvNet with Spatial Batch Norm in NumPy. The update rules used for training are SGD, SGD+Momentum, RMSProp and Adam. Implemented three block ResNet in PyTorch, with 10 epochs of training achieves 73.60% accuracy on test set.
User: srinadhu
Home Page: http://cs231n.github.io/assignments2017/assignment2/
fully-connected-deep-neural-network,This repository contains code that implemented Mask Detection using MobileNet as the base model and Neural Network as the head model. Code draws a rectangular box over the person's face in red if no mask, green if the mask is on, with 99% accuracy in real-time using a live webcam. Refer to README for demo
User: tejas-ta
Home Page: https://github.com/Tejas-TA/Face-Mask-Detection-Real-Time-Computer-Vision
fully-connected-deep-neural-network,Using different ML models with different optimizers (pytorch)
User: yaronso
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