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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
In this paper, visual perception computational models oriented deep learning are investigated from the biological visual mechanism and computational vision theory systematically.  ...  Computational models inspired by visual perception have the characteristics of complexity and diversity, as they come from many subjects such as cognition science, information science, and artificial intelligence  ...  Based on biological mechanisms, visual attention mechanisms are mainly divided into bottom-up attention and top-down attention [26] , and based on theses two kinds of attention, many researches have been  ... 
arXiv:2109.03391v1 fatcat:xtgda2x6azd2laun45tqfj77gi

Bottom-up visual attention model for still image: a preliminary study

Adhi Prahara, Murinto Murinto, Dewi Pramudi Ismi
2020 IJAIN (International Journal of Advances in Intelligent Informatics)  
The study compares some models at each stage and observes whether the stage is inspired by biological architecture, concept, or behavior of human visual attention.  ...  The preliminary study briefly covers from the biological perspective of visual attention, including visual pathway, the theory of visual attention, to the computational model of bottom-up visual attention  ...  Recently, the rising of deep learning influences the bottomup salient object detection model into top-down or hybrid approach.  ... 
doi:10.26555/ijain.v6i1.469 fatcat:blbdxhlzjjcvhpm7dtimctgepq

What Can We Learn from Biological Vision Studies for Human Motion Segmentation? [chapter]

Cheng Chen, Guoliang Fan
2006 Lecture Notes in Computer Science  
We attempt to develop a comprehensive computational model that involves both bottom-up and top-down processing and is deeply inspired by biological motion perception.  ...  Specifically, we discuss the roles and interactions of bottom-up and top-down processes in visual perception processing as well as how to combine them synergistically in one computational model to guide  ...  In this work, we will review two types of biological vision studies, i.e., general perception and biological movement perception, based on which we attempt to develop a comprehensive computational model  ... 
doi:10.1007/11919629_79 fatcat:2uark6vbibdbjosbrz6p3pqpxi

Salience Models: A Computational Cognitive Neuroscience Review

Sofia Krasovskaya, W. Joseph MacInnes
2019 Vision  
We present a review of recent approaches to modelling salience, starting from direct variations of the Itti and Koch salience model to sophisticated deep-learning architectures, and discuss the models  ...  One of the most recent trends has been to adopt the computational power of deep learning neural networks; however, this has also shifted their primary focus to spatial classification.  ...  Thus, we highlight the following groups of models: models directly inspired by the Itti and Koch architecture, biologically driven models, top-down models, models based on the dorsal and ventral pathways  ... 
doi:10.3390/vision3040056 pmid:31735857 pmcid:PMC6969943 fatcat:3xvjv3ypdfdxjfwmmtj6mfpvla

A Biologically-Inspired Model for Recognition of Overlapped Patterns [chapter]

Mohammad Saifullah
2012 Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering  
In this paper a biologically-inspired model for recognition of overlapped patterns is proposed.  ...  We hypothesize that dorsal pathway, in addition to encoding the spatial information, learns the shape representation of the patterns and, later uses this knowledge as a top-down guidance signal to segment  ...  Grossberg [15] presented a biologically-inspired model of the visual cortex that approaches the figure-ground separation as an interactive process.  ... 
doi:10.1007/978-3-642-32711-7_12 fatcat:ymwikliajjgzfcu6o7qbgzbmrq

Learning where to look with movement-based intrinsic motivations: A bio-inspired model

Valerio Sperati, Gianluca Baldassarre
2014 4th International Conference on Development and Learning and on Epigenetic Robotics  
The model is formed by bottom-up attentional components, exploiting the intrinsic properties of the scene, and top-down attentional components, learning under the guidance of movement-based intrinsic motivation  ...  The model also allows the presentation of a wider research agenda directed to build biologically plausible models of the interaction between overt attention control and intrinsic motivations.  ...  received funds from the European Commission under the 7th Framework Programme (FP7/2007-2013), ICT Challenge 2 "Cognitive Systems and Robotics", project "IM-CLeVeR -Intrinsically Motivated Cumulative Learning  ... 
doi:10.1109/devlrn.2014.6983024 dblp:conf/icdl-epirob/SperatiB14 fatcat:s2uyphyisbduhgmcyyl3uwjchq

Attention-based Assisted Excitation for Salient Object Detection [article]

Saeed Masoudnia, Melika Kheirieh, Abdol-Hossein Vahabie, Babak Nadjar Araabi
2020 arXiv   pre-print
In this paper, object-based attention in human visual cortex inspires us to introduce a mechanism for modification of activations in feature maps of CNNs.  ...  This mechanism is specifically inspired by attention-based gain modulation in object-based attention in brain. It facilitates figure-ground segregation in the visual cortex.  ...  Learning Technique to Improve Object Detectors" [34] .  ... 
arXiv:2003.14194v2 fatcat:xmsmq2usz5hczd6e4tvu7vv7ku

Biologically Inspired Visual System Architecture for Object Recognition in Autonomous Systems

Dan Malowany, Hugo Guterman
2020 Algorithms  
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  ...  In addition, the human visual system continuously updates its knowledge about the world based on the gaps between its prediction and the visual feedback.  ...  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

Bio-inspired visual attention for silicon retinas based on spiking neural networks applied to pattern classification [article]

Amélie Gruel, Jean Martinet
2021 arXiv   pre-print
Visual attention can be defined as the behavioral and cognitive process of selectively focusing on a discrete aspect of sensory cues while disregarding other perceivable information.  ...  In this paper, we review the biological background behind the attentional mechanism, and introduce a case study of event videos classification with SNNs, using a biology-grounded low-level computational  ...  The first dichotomy can be defined between top-down and bottom-up attention. The top-down one corresponds to a selective type of attention depending on a previously set motivation or rule.  ... 
arXiv:2105.14753v1 fatcat:iwpob5wx6bc6tpjpzee6jz5ija

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

Dan Malowany, Hugo Guterman
2020 arXiv   pre-print
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  ...  In addition, the human visual system continuously updates its knowledge about the world based on the gaps between its prediction and the visual feedback.  ...  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

WWN-2: A biologically inspired neural network for concurrent visual attention and recognition

Zhengping Ji, Juyang Weng
2010 The 2010 International Joint Conference on Neural Networks (IJCNN)  
This architecture enables three types of attention: feature-based bottom-up attention, position-based top-down attention, and object-based top-down attention, as three possible information flows through  ...  Inspired by the brain's dorsal and ventral pathways in cortical visual processing, we present a neuromorphic architecture, called Where-What Network 2 (WWN-2), to integrate object attention and recognition  ...  The model displayed positionbased and object-based covert visual search by using attentional top-down feedback.  ... 
doi:10.1109/ijcnn.2010.5596778 dblp:conf/ijcnn/JiW10 fatcat:3jtvzt6d45acraiawxc6fvl2ta

Predicting eye fixations using convolutional neural networks

Nian Liu, Junwei Han, Dingwen Zhang, Shifeng Wen, Tianming Liu
2015 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
In higher layers, the proposed Mr-CNN can learn diverse high-level top-down visual features due to its deep architecture.  ...  Visual causes versus correlates of attentional selection in dynamic scenes. Figure 1 : Diagram of our Mr-CNN based model.  ... 
doi:10.1109/cvpr.2015.7298633 dblp:conf/cvpr/LiuHZWL15 fatcat:qp5moaefivgyxjix6klkpjtxu4

Editorial: Hierarchical Object Representations in the Visual Cortex and Computer Vision

Antonio J. Rodríguez-Sánchez, Mazyar Fallah, Aleš Leonardis
2015 Frontiers in Computational Neuroscience  
While these studies have focused on using biologically-inspired visual processing in computational models, Bertalmío (2014) worked in reverse by taking an image processing technique used for local histogram  ...  On the same topic, Tal and Bar (2014) explored the role of top-down mechanisms which bias the processing of the incoming visual information and facilitate fast and robust recognition.  ...  Conflict of Interest Statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest  ... 
doi:10.3389/fncom.2015.00142 pmid:26635595 pmcid:PMC4653288 fatcat:m6imrk7ptnbwbgsmphvddirf3m

Online learning of task-driven object-based visual attention control

Ali Borji, Majid Nili Ahmadabadi, Babak Nadjar Araabi, Mandana Hamidi
2010 Image and Vision Computing  
From this information, a state is derived in the decision making and learning layer. Top-down attention is learned by the U-TREE algorithm which successively grows an object-based binary tree.  ...  A biologically-motivated computational model for learning task-driven and objectbased visual attention control in interactive environments is proposed. Our model consists of three layers.  ...  37, 41 3,15,16,20,27, 29,30,34,38,42 6,14,22 L R 4,7,11,17,23,39,43 o A biologically inspired model for top-down object-based visual attention control was designed and partially implemented  ... 
doi:10.1016/j.imavis.2009.10.006 fatcat:swhyzopwabh6jih6iuzkw72cta

Biological visual attention guided automatic image segmentation with application in satellite imaging

M. I. Sina, A.-M. Cretu, P. Payeur
2012 Human Vision and Electronic Imaging XVII  
This paper outlines some of the difficulties that the current generation of visual attention-inspired models encounter when dealing with satellite images.  ...  Taking inspiration from the significantly superior performance of humans to extract and interpret visual information, the exploitation of biological visual mechanisms can contribute to the improvement  ...  IMPLEMENTATION OF A BIOLOGICALLY-INSPIRED VISUAL ATTENTION MODEL AND ITS EVALUATION FOR SATELLITE IMAGES The computational attention model implemented (in C++ and OpenCV software library 13 ) and tested  ... 
doi:10.1117/12.911996 dblp:conf/hvei/SinaCP12 fatcat:7xyto2nfrne6jc7cbajlwhoieu
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