Visualizing and Interpreting Convolutional Neural Network

Published: 09 Oct 2015 Category: deep_learning


Deconvolutional Networks

Visualizing and Understanding Convolutional Network

Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Understanding Deep Image Representations by Inverting Them

deepViz: Visualizing Convolutional Neural Networks for Image Classification

Inverting Convolutional Networks with Convolutional Networks

Understanding Neural Networks Through Deep Visualization

Visualizing Higher-Layer Features of a Deep Network

Generative Modeling of Convolutional Neural Networks

Understanding Intra-Class Knowledge Inside CNN

Learning FRAME Models Using CNN Filters for Knowledge Visualization

Convergent Learning: Do different neural networks learn the same representations?

Visualizing and Understanding Deep Texture Representations

Visualizing Deep Convolutional Neural Networks Using Natural Pre-Images

An Interactive Node-Link Visualization of Convolutional Neural Networks

Learning Deep Features for Discriminative Localization

Multifaceted Feature Visualization: Uncovering the Different Types of Features Learned By Each Neuron in Deep Neural Networks

A New Method to Visualize Deep Neural Networks

A Taxonomy and Library for Visualizing Learned Features in Convolutional Neural Networks

VisualBackProp: visualizing CNNs for autonomous driving

VisualBackProp: efficient visualization of CNNs

Grad-CAM: Why did you say that? Visual Explanations from Deep Networks via Gradient-based Localization

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

Grad-CAM: Why did you say that?

Visualizing Residual Networks

Visualizing Deep Neural Network Decisions: Prediction Difference Analysis

ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models

Picasso: A Neural Network Visualizer

CNN Fixations: An unraveling approach to visualize the discriminative image regions

A Forward-Backward Approach for Visualizing Information Flow in Deep Networks

Using KL-divergence to focus Deep Visual Explanation

An Introduction to Deep Visual Explanation

Visual Explanation by Interpretation: Improving Visual Feedback Capabilities of Deep Neural Networks

Visualizing the Loss Landscape of Neural Nets

Visualizing Deep Similarity Networks

Interpreting Convolutional Neural Networks

Network Dissection: Quantifying Interpretability of Deep Visual Representations

Interpreting Deep Visual Representations via Network Dissection

Methods for Interpreting and Understanding Deep Neural Networks

SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability

Towards Interpretable Deep Neural Networks by Leveraging Adversarial Examples

Interpretable Convolutional Neural Networks

Interpreting Convolutional Neural Networks Through Compression

Interpreting Deep Neural Networks

Interpreting CNNs via Decision Trees

Visual Interpretability for Deep Learning: a Survey

Interpreting Deep Classifier by Visual Distillation of Dark Knowledge

How convolutional neural network see the world - A survey of convolutional neural network visualization methods

Understanding Regularization to Visualize Convolutional Neural Networks

Deeper Interpretability of Deep Networks

Interpretable CNNs

Explaining AlphaGo: Interpreting Contextual Effects in Neural Networks

Interpretable BoW Networks for Adversarial Example Detection

Deep Features Analysis with Attention Networks

Understanding Neural Networks via Feature Visualization: A survey

Explaining Neural Networks via Perturbing Important Learned Features

Interpreting Adversarially Trained Convolutional Neural Networks


Interactive Deep Neural Net Hallucinations


draw_convnet: Python script for illustrating Convolutional Neural Network (ConvNet)

Caffe prototxt visualization

Keras Visualization Toolkit

mNeuron: A Matlab Plugin to Visualize Neurons from Deep Models




“Visualizing GoogLeNet Classes”

Visualizing CNN architectures side by side with mxnet

How convolutional neural networks see the world: An exploration of convnet filters with Keras

Visualizing Deep Learning with t-SNE (Tutorial and Video)

Peeking inside Convnets

Visualizing Features from a Convolutional Neural Network

Visualizing Deep Neural Networks Classes and Features

Visualizing parts of Convolutional Neural Networks using Keras and Cats

Visualizing convolutional neural networks


Topological Visualisation of a Convolutional Neural Network

Visualization of Places-CNN and ImageNet CNN

Visualization of a feed forward Neural Network using MNIST dataset

CNNVis: Towards Better Analysis of Deep Convolutional Neural Networks.

Quiver: Interactive convnet features visualization for Keras