2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDMLR-APPL-IP-3.9
Paper Title HUMAN VISION-LIKE ROBUST OBJECT RECOGNITION
Authors Peng Kang, Northwestern University, United States; Hao Hu, University of British Columbia, Canada; Srutarshi Banerjee, Henry Chopp, Aggelos K. Katsaggelos, Oliver Cossairt, Northwestern University, United States
SessionMLR-APPL-IP-3: Machine learning for image processing 3
LocationArea F
Session Time:Tuesday, 21 September, 08:00 - 09:30
Presentation Time:Tuesday, 21 September, 08:00 - 09:30
Presentation Poster
Topic Applications of Machine Learning: Machine learning for image processing
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Abstract Previous research always solely utilizes Artificial Neural Networks (ANNs) or Spiking Neural Networks (SNNs) for object recognition. However, evidence in neuroscience suggests that the visual processing in human vision is performed hierarchically in the combination of analog and digital processing. To construct a more human vision-like object recognition system, we propose a general hierarchical ANN-SNN model. We evaluate our model and its variants on two popular datasets to show its effectiveness, robustness, efficiency, and generality. Extensive experiments clearly demonstrate the superiority of our proposed models for robust object recognition.