An implementation of DetNet with Keras.
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Updated
Nov 20, 2018 - Python
An implementation of DetNet with Keras.
Numerical Computation of Receptive Field in Pytorch
An implementation of Olshausen and Field (96) in PyTorch
Python program to calculate and visualize effective receptive field of a layer in deep convolution neural network
Program implements a convolutional neural network for classifying images of numbers in the MNIST dataset as either even or odd using GPU framework.
Compute the theoretical/analytical receptive field of deep neural networks in plain Python.
Often we spend lots of time calculating the Receptive field of a CNN model.This Module can calculate the receptive field, Output image size from a model object
Numerically compute the Receptive Field of a conv block in PyTorch
Implementation of research paper : "PraNet: Parallel Reverse Attention Network for Polyp Segmentation" in Tensorflow
This repo contains submissions of all assignments of a EVA by TSAI
A simple receptive field calculator for convolutional neural networks (CNN).
Compute receptive fields as input masks for single neurons in any CNN written in PyTorch.
A repository to work on Deep Learning course. ANN, CNN, VGG, ResNet, etc.
Extract the receptive field of a fully connected cnn.
This simple web app allows to user to map the receptive field of a chosen artificial neuron in AlexNet, Vgg16, and ResNet18. Deployed on GitHub Pages, but also under construction.
This repository serves as a collection of implementations and resources for various computational neuroscience techniques, including Hopfield's network,hebbian learning and common spatial patterns etc.
Seamless analysis of your PyTorch models (RAM usage, FLOPs, MACs, receptive field, etc.)
High-Performance Transformers for Table Structure Recognition Need Early Convolutions
A fast and versatile implementation of spike-triggered non-negative matrix factorization (STNMF) based on accelerated/fast HALS algorithms
Compute CNN receptive field size in pytorch in one line
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