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Visual Sensation and Perception Computational Models for Deep Learning: State of the art, Challenges and Prospects [article]

Bing Wei, Yudi Zhao, Kuangrong Hao, Lei Gao
2021 arXiv   pre-print
Through this survey, it will provide a comprehensive reference for research in this direction.  ...  In this paper, visual perception computational models oriented deep learning are investigated from the biological visual mechanism and computational vision theory systematically.  ...  [129] presents ideas and plans for creating a decentralized model for social signal integration inspired by computational models for multi-sensory integration in neuroscience.  ... 
arXiv:2109.03391v1 fatcat:xtgda2x6azd2laun45tqfj77gi

Biologically Inspired Intensity and Depth Image Edge Extraction

Dermot Kerr, Sonya Coleman, Thomas Martin McGinnity
2018 IEEE Transactions on Neural Networks and Learning Systems  
In this paper, we present a depth and intensity image feature extraction approach that has been inspired by biological vision systems.  ...  Through the use of biologically inspired spiking neural networks we emulate functional computational aspects of biological visual systems.  ...  Similarly, the bio-inspired scene classification [25] uses a three-layer neural network to classify scenes based on visual features.  ... 
doi:10.1109/tnnls.2018.2797994 pmid:29994457 fatcat:66mdav5fafarnowuo6g7e6qgv4

HMAX-S: Deep scale representation for biologically inspired image categorization

Christian Theriault, Nicolas Thome, Matthieu Cord
2011 2011 18th IEEE International Conference on Image Processing  
This paper presents an improvement on a biologically inspired network for image classification.  ...  Previous models have used a multiscale and multi-orientation architecture to gain robustness to transformations and to extract complex visual features.  ...  One biologically inspired network which has received a great deal of attention comes from the HMAX model of Riesenhuber&al [3] .  ... 
doi:10.1109/icip.2011.6115663 dblp:conf/icip/TheriaultTC11 fatcat:lmcesge4f5e2pewacylywi6zly

A novel method of aerial image classification based on attention-based local descriptors

Sheng Xu, Tao Fang, Hong Huo, Deren Li
2009 Procedia Earth and Planetary Science  
This paper proposes a novel method for object-based classification in very high spatial resolution aerial image.  ...  Unlike the previous work on detection of the local regions, a biologically motivated selective attention model is presented in this paper, since not all the local regions are important for describing the  ...  We have given a biologically inspired attention computation model, and have extracted evenly regular grids from the salient regions.  ... 
doi:10.1016/j.proeps.2009.09.174 fatcat:kjzmssb54rgtnbqm6q2vh4ltpu

Classification of marine organisms in underwater images using CQ-HMAX biologically inspired color approach

Sepehr Jalali, Paul J. Seekings, Cheston Tan, Hazel Z. W. Tan, Joo-Hwee Lim, Elizabeth A. Taylor
2013 The 2013 International Joint Conference on Neural Networks (IJCNN)  
We evaluate several different classification approaches on this dataset, and show that CQ-HMAX, our new biologically inspired approach to utilizing color information for object and scene recognition, that  ...  Visual classification of marine organisms is necessary for population estimates of individual species of corals or other benthic organisms.  ...  Acknowledgements The photos were taken by Jim Wong who was working for the Marine Mammal Research Laboratory, Tropical Marine Science Institute, NUS.  ... 
doi:10.1109/ijcnn.2013.6707084 dblp:conf/ijcnn/JalaliSTTLT13 fatcat:tnoxl2s7angvdd22fcmpcw7nui

Enhancing object recognition for humanoid robots through time-awareness

Andreas Holzbach, Gordon Cheng
2013 2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids)  
In this paper, we present a biologically-inspired object recognition system for humanoid robots.  ...  Our approach is based on a hierarchical model of the visual cortex for feature extraction and rapid scene categorization of natural images.  ...  which gain their inspiration and functionality from biological models.  ... 
doi:10.1109/humanoids.2013.7029983 fatcat:nh5r5gj2ibaqpcvm233abduvja

A Novel Biologically Mechanism-Based Visual Cognition Model--Automatic Extraction of Semantics, Formation of Integrated Concepts and Re-selection Features for Ambiguity [article]

Peijie Yin, Hong Qiao, Wei Wu, Lu Qi, YinLin Li, Shanlin Zhong, Bo Zhang
2016 arXiv   pre-print
In this paper, inspired by features of human recognition process and their biological mechanisms, a new integrated and dynamic framework is proposed to mimic the semantic extraction, concept formation  ...  Many related models have been proposed, such as computational visual cognition models, computational motor control models, integrations of both and so on.  ...  CONCLUSION In this paper, a novel biologically inspired model is proposed for robust visual recognition, mimicking the visual processing system in human brain.  ... 
arXiv:1603.07886v1 fatcat:f2dzur7tzzgxni26w5lkc2bj2u

Bio-Inspired Optic Flow from Event-Based Neuromorphic Sensor Input [chapter]

Stephan Tschechne, Roman Sailer, Heiko Neumann
2014 Lecture Notes in Computer Science  
Computational models of visual processing often use framebased image acquisition techniques to process a temporally changing stimulus.  ...  We introduce a new approach for the modelling of cortical mechanisms of motion detection along the dorsal pathway using this type of representation.  ...  ., Bruhn, A., Papenberg, N., Weickert, J.: High Accuracy Optical Flow Estimation Based on a Theory for Warping. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3024, pp. 25-36.  ... 
doi:10.1007/978-3-319-11656-3_16 fatcat:adym3otnfrhd5ovkm562gmy77m

2018 IndexIEEE Transactions on Cognitive and Developmental SystemsVol. 10

2018 IEEE Transactions on Cognitive and Developmental Systems  
., +, TCDS March 2018 72-87 A Novel Biologically Inspired Visual Cognition Model: Automatic Extraction of Semantics, Formation of Integrated Concepts, and Reselection Features for Ambiguity.  ...  ., +, TCDS Sept. 2018 810-822 A Novel Biologically Inspired Visual Cognition Model: Automatic Ex- traction of Semantics, Formation of Integrated Concepts, and Reselection Features for Ambiguity.  ... 
doi:10.1109/tcds.2019.2892259 fatcat:b2njmkdqk5azpmll74ucef3h5m

Editorial: Modeling of Visual Cognition, Body Sense, Motor Control and Their Integrations

Hong Qiao, Li Hu
2016 Frontiers in Computational Neuroscience  
This article provides a potential structure for visual-motor interaction modeling in bio-inspired imitation learning.  ...  The authors analyzed the functions of neurons in VisNet model through a biologically plausible process of unsupervised competitive learning and self-organization both with realistic and natural images.  ...  COMPUTATIONAL MODELING OF VISUAL PROCESSING BIO-INSPIRED VISUAL MODELS Li et al. proposed an enhanced HMAX model for image categorization.  ... 
doi:10.3389/fncom.2016.00142 pmid:28082893 pmcid:PMC5187263 fatcat:sqwo4mxdjra6dfrxloqc3bhf7y

IEEE Access Special Section Editorial: Biologically Inspired Image Processing Challenges and Future Directions

Jiachen Yang, Qinggang Meng, Maurizio Murroni, Shiqi Wang, Feng Shao
2020 IEEE Access  
Although it is a challenge, it can also be considered as an opportunity which utilizes biologically inspired ideas.  ...  images by simulating binocular interaction and depth perception based on a cyclopean image from a novel binocular combination model, and a depth binocular combination model from a depth synthesized procedure  ... 
doi:10.1109/access.2020.3015372 fatcat:styxiguqlnaprclkiamogmjc24

A Data-Driven and Biologically Inspired Preprocessing Scheme to Improve Visual Object Recognition

Zahra Sadat Shariatmadar, Karim Faez, Akbar S. Namin
2021 Computational Intelligence and Neuroscience  
In this paper, we propose a new, simple, and biologically inspired pre processing technique by using the data-driven mechanism of visual attention.  ...  Due to recent advances in visual neuroscience, the researchers tend to extend biologically plausible schemes to improve the accuracy of object recognition.  ...  Acknowledgments e authors acknowledge the Amirkabir University of Technology (Tehran Poly Technique) for financially supporting and processing equipment of this work.  ... 
doi:10.1155/2021/6699335 fatcat:2yybdib3bjes5luhx7cyj2xtiq

Biologically Inspired Visual System Architecture for Object Recognition in Autonomous Systems

Dan Malowany, Hugo Guterman
2020 Algorithms  
recognition models, e.g., deep CNNs.  ...  In an attempt to bring computer vision algorithms closer to the capabilities of a human operator, the mechanisms of the human visual system was analyzed in this work.  ...  Acknowledgments: Special thanks go to Moshe Bar from the Gonda Brain Research Center in Bar-Ilan University, for his feedback and useful insights on the human visual system.  ... 
doi:10.3390/a13070167 fatcat:ufyjjfcjnva2deam5kyhkzvzd4

Biologically Inspired Visual System Architecture for Object Recognition in Autonomous Systems [article]

Dan Malowany, Hugo Guterman
2020 arXiv   pre-print
In an attempt to bring computer vision algorithms closer to the capabilities of a human operator, the mechanisms of the human visual system was analyzed in this work.  ...  In this work, an architecture was designed that aims to integrate the concepts behind the top-down prediction and learning processes of the human visual system with the state of the art bottom-up object  ...  Design of a biologically inspired architecture for integration of top-down and bottom-up processes into one holistic solution (section 4). 2.  ... 
arXiv:2002.03472v2 fatcat:k3y6f7turrgjvk47g3m53olbxe

Biologically inspired vision systems in robotics

Antonio Fernández-Caballero, José Manuel Ferrández
2017 International Journal of Advanced Robotic Systems  
The next paper 7 introduces a self-learning method of robotic experience for building episodic cognitive map using biologically inspired episodic memory.  ...  The rover visual system must be able to follow quantified information gradients for smooth tracking in the visual field with limited information from images and delayed positional feedback caused by long  ... 
doi:10.1177/1729881417745947 fatcat:n7guiw7n2zbvhjaifigyw7k3l4
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