Invariant Object Recognition with Slow Feature Analysis

No abstract is available for this paper.

• Publication year

  2008

• Venue

  International Conference on Artificial Neural Networks

• Publication date

  2008-09-03

• Fields of study

  Computer Science

• Identifiers
  DOI 10.1007/978-3-540-87536-9_98
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Slowness: An Objective for Spike-Timing–Dependent Plasticity?

  2007cited by this paper
• Slowness and Sparseness Lead to Place, Head-Direction, and Spatial-View Cells

  2007cited by this paper
• Slow feature analysis yields a rich repertoire of complex cell properties.

  2005cited by this paper
• Slow Feature Analysis: A Theoretical Analysis of Optimal Free Responses

  2003cited by this paper
• Quadratic forms in natural images

  2003cited by this paper
• Computational neuroscience of vision

  2002cited by this paper
• Slow Feature Analysis: Unsupervised Learning of Invariances

  2002cited by this paper
• Extracting Slow Subspaces from Natural Videos Leads to Complex Cells

  2001cited by this paper
• Artificial Neural Networks — ICANN 2001

  2001cited by this paper
• Invariant face and object recognition in the visual system.

  1997cited by this paper
• A learning rule for extracting spatio-temporal invariances

  1995cited by this paper
• Neurophysiological mechanisms underlying face processing within and beyond the temporal cortical visual areas.

  1992cited by this paper
• Learning Invariance from Transformation Sequences

  1991cited by this paper

• Human Activity Recognition Using Rotation Invariant Radial Fourier Profile Features

  2024cites this paper
• Interpretable Brain-Inspired Representations Improve RL Performance on Visual Navigation Tasks

  2024cites this paper
• Probabilistic Adaptive Slow Feature Analysis for State Estimation and Classification

  2024cites this paper
• Toward a computational theory of manifold untangling: from global embedding to local flattening

  2023cites this paper
• The neuroconnectionist research programme

  2022cites this paper
• Slow Down to Go Better: A Survey on Slow Feature Analysis

  2022cites this paper
• Mutual Information Induced Slow-Feature Analysis of Nonlinear Dynamic Systems and the Application in Soft Sensors

  2022cites this paper
• Slow Feature Extraction Algorithm Based on Visual Selection Consistency Continuity and Its Application

  2021cites this paper
• Dimensions of Timescales in Neuromorphic Computing Systems

  2021cites this paper
• Design and Application of a Slow Feature Algorithm Coupling Visual Selectivity and Multiple Long Short-Term Memory Networks

  2021cites this paper
• Monitoring of Industrial Processes via Non-stationary Probabilistic Slow Feature Analysis Machine Learning Algorithm

  2020cites this paper
• 3 Embedding Dynamic Field Theory in Neurophysiology

  2019cites this paper
• Design and Application of an Adaptive Slow Feature Extraction Algorithm for Natural Images Based on Visual Invariance

  2019cites this paper
• Frequency-based slow feature analysis

  2019cites this paper
• Temporally Coherent Visual Representations for Dimensional Affect Recognition

  2019cites this paper
• Adapting deep neural networks as models of human visual perception

  2018cites this paper
• Unsupervised Deep Slow Feature Analysis for Change Detection in Multi-Temporal Remote Sensing Images

  2018cites this paper
• Sensorimotor Robot Policy Training using Reinforcement Learning

  2018cites this paper
• Global Navigation Using Predictable and Slow Feature Analysis in Multiroom Environments, Path Planning and Other Control Tasks

  2018cites this paper
• Locally distributed spatial navigation in a scale-space model for grid cells

  2018cites this paper
• Deep Neural Networks in Computational Neuroscience

  2018cites this paper
• Belief Propagation for Probabilistic Slow Feature Analysis

  2017cites this paper
• Feature Sequence Representation Via Slow Feature Analysis For Action Classification

  2017cites this paper
• The use of deep learning to solve invariance issues in object recognition

  2017cites this paper
• A computational exploration of complementary learning mechanisms in the primate ventral visual pathway.

  2016cites this paper
• Pose-Invariant Object Recognition for Event-Based Vision with Slow-ELM

  2016cites this paper
• Improved graph-based SFA: information preservation complements the slowness principle

  2016cites this paper
• Multimodal Object Recognition via deep learning to implement invariance

  2016cites this paper
• Embedding Dynamic Field Theory in Neurophysiology

  2015cites this paper
• Uncorrelated slow feature discriminant analysis using globality preserving projections for feature extraction

  2015cites this paper
• Adaptive unsupervised slow feature analysis for feature extraction

  2015cites this paper
• Towards an Embodied Developing Vision System

  2015cites this paper
• Image completion with multi-image based on entropy reduction

  2015cites this paper
• Online Kernel Slow Feature Analysis for Temporal Video Segmentation and Tracking

  2015cites this paper
• Probabilistic slow feature analysis‐based representation learning from massive process data for soft sensor modeling

  2015cites this paper
• Perceptual Principles for Video Classification With Slow Feature Analysis

  2014cites this paper
• DL-SFA: Deeply-Learned Slow Feature Analysis for Action Recognition

  2014cites this paper
• Multi-option image completion based on semantic matching image

  2014cites this paper
• Extracting Latent Dynamics from Multi-dimensional Data by Probabilistic Slow Feature Analysis

  2013cites this paper
• Dynamic Scene Classification: Learning Motion Descriptors with Slow Features Analysis

  2013cites this paper
• Pylearn2: a machine learning research library

  2013cites this paper
• A Unifying Approach to High- and Low-Level Cognition

  2013cites this paper
• How to solve classification and regression problems on high-dimensional data with a supervised extension of slow feature analysis

  2013influential citation
• Deep Learning of Invariant Features via Simulated Fixations in Video

  2012cites this paper
• Hierarchical Slow Feature Analysis on visual stimuli and top-down reconstruction

  2012influential citation
• Exploring the slowness principle in the auditory domain

  2012cites this paper
• Slow Feature Analysis for Human Action Recognition

  2012cites this paper
• Heuristic Evaluation of Expansions for Non-linear Hierarchical Slow Feature Analysis

  2011cites this paper
• On the Relation of Slow Feature Analysis and Laplacian Eigenmaps

  2011cites this paper
• The slowness principle: SFA can detect different slow components in non-stationary time series

  2011influential citation
• Monocular road segmentation using slow feature analysis

  2011cites this paper
• A cortical model of object perception based on Bayesian networks and belief propagation.

  2011cites this paper
• Forward engineering object recognition : a scalable approach

  2011cites this paper
• Making a robotic scene representation accessible to feature and label queries

  2011cites this paper
• Unsupervised learning of visual invariance with temporal coherence

  2011cites this paper
• Reinforcement Learning on Slow Features of High-Dimensional Input Streams

  2010influential citation
• Gender and Age Estimation from Synthetic Face Images

  2010cites this paper
• Learning Generic Invariances in Object Recognition: Translation and Scale

  2010cites this paper
• A Neural Network Model of

  2010cites this paper
• Cortex-inspired goal-directed recurrent networks for developmental visual attention and recognition with complex backgrounds

  2010cites this paper
• Action recognition in video

  2010cites this paper
• Gender and Age Estimation from Synthetic Face Images with Hierarchical Slow Feature Analysis

  2010cites this paper
• Top-down connections as abstract and temporal context for self-organization and categorization

  2010cites this paper
• A Theoretical Basis for Emergent Pattern Discrimination in Neural Systems Through Slow Feature Extraction

  2010cites this paper
• Learning Invariant Visual Shape Representations from Physics

  2010cites this paper
• Visualization of higher-level receptive fields in a hierarchical model of the visual system

  2009cites this paper
• A High-Throughput Screening Approach to Discovering Good Forms of Biologically Inspired Visual Representation

  2009cites this paper
• A Structured Model of Video Reproduces Primary Visual Cortical Organisation

  2009cites this paper
• Reinforcement learning on complex visual stimuli

  2009cites this paper
• Modular Toolkit for Data Processing (MDP): A Python Data Processing Framework

  2008cites this paper
• Learning in the Loop : Fast Explorative Learning of Inverse Models in High Dimensions

  year unknowncites this paper
• Ieee Transactions on Intelligent Transportation Systems 1 Monocular Road Terrain Detection by Combining Visual and Spatial Information

  year unknowncites this paper