4.7 Article

Exploiting auto-encoders and segmentation methods for middle-level explanations of image classification systems

Related references

Note: Only part of the references are listed.
Article Computer Science, Information Systems

Improved clustering algorithms for image segmentation based on non-local information and back projection

Xiaofeng Zhang et al.

Summary: This paper proposes an improved image segmentation schema and presents two improved clustering algorithms that consider self-similarity and back projection simultaneously to enhance robustness, balancing noise restraining and detail retention in segmentation of complex images.

INFORMATION SCIENCES (2021)

Article Multidisciplinary Sciences

A framework to identify structured behavioral patterns within rodent spatial trajectories

Francesco Donnarumma et al.

Summary: This study introduces a framework to quantify rodent behavior during spatial navigation, assuming that rodent behavior is characterized by a small number of motor primitives. The motor primitives are extracted using a sparse dictionary learning method, allowing for the reconstruction of past trajectories and prediction of novel ones.

SCIENTIFIC REPORTS (2021)

Review Computer Science, Artificial Intelligence

A survey on modern trainable activation functions

Andrea Apicella et al.

Summary: In recent years, there has been a renewed interest in trainable activation functions, which can be trained during the learning process to improve neural network performance. Various models of trainable activation functions have been proposed in the literature, many of which are equivalent to adding neuron layers with fixed activation functions and simple local rules.

NEURAL NETWORKS (2021)

Article Computer Science, Artificial Intelligence

Comparison of export and outward foreign direct investment models of Chinese enterprises based on quantitative algorithm

Danqi Li et al.

NEURAL COMPUTING & APPLICATIONS (2020)

Article Computer Science, Artificial Intelligence

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

Alejandro Barredo Arrieta et al.

INFORMATION FUSION (2020)

Article Computer Science, Artificial Intelligence

Middle-Level Features for the Explanation of Classification Systems by Sparse Dictionary Methods

A. Apicella et al.

INTERNATIONAL JOURNAL OF NEURAL SYSTEMS (2020)

Article Computer Science, Artificial Intelligence

Image segmentation using dense and sparse hierarchies of superpixels

Felipe Lemes Galvao et al.

PATTERN RECOGNITION (2020)

Article Computer Science, Artificial Intelligence

Explanation in artificial intelligence: Insights from the social sciences

Tim Miller

ARTIFICIAL INTELLIGENCE (2019)

Article Computer Science, Information Systems

Disentangled Variational Auto-Encoder for semi-supervised learning

Yang Li et al.

INFORMATION SCIENCES (2019)

Article Multidisciplinary Sciences

Definitions, methods, and applications in interpretable machine learning

W. James Murdoch et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2019)

Article Computer Science, Information Systems

A hierarchical prototype-based approach for classification

Xiaowei Gu et al.

INFORMATION SCIENCES (2019)

Article Engineering, Electrical & Electronic

Methods for interpreting and understanding deep neural networks

Gregoire Montavon et al.

DIGITAL SIGNAL PROCESSING (2018)

Article Engineering, Electrical & Electronic

Unsupervised image segmentation via Stacked Denoising Auto-encoder and hierarchical patch indexing

Jun Yu et al.

SIGNAL PROCESSING (2018)

Review Computer Science, Information Systems

Visual interpretability for deep learning: a survey

Quan-shi Zhang et al.

FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING (2018)

Article Computer Science, Information Systems

Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)

Amina Adadi et al.

IEEE ACCESS (2018)

Article Computer Science, Artificial Intelligence

Explaining nonlinear classification decisions with deep Taylor decomposition

Gregoire Montavon et al.

PATTERN RECOGNITION (2017)

Article Computer Science, Artificial Intelligence

Evaluating the Visualization of What a Deep Neural Network Has Learned

Wojciech Samek et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2017)

Article Computer Science, Information Systems

An efficient image segmentation method based on a hybrid particle swarm algorithm with learning strategy

Hao Gao et al.

INFORMATION SCIENCES (2016)

Article Computer Science, Information Systems

Advertiser-centric approach to understand user click behavior in sponsored search

Sungchul Kim et al.

INFORMATION SCIENCES (2014)

Review Computer Science, Artificial Intelligence

Representation Learning: A Review and New Perspectives

Yoshua Bengio et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2013)

Article Computer Science, Artificial Intelligence

Scale-sets image analysis

Laurent Guigues et al.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2006)