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

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 147459-147462
Author(s):  
Jiachen Yang ◽  
Qinggang Meng ◽  
Maurizio Murroni ◽  
Shiqi Wang ◽  
Feng Shao
Keyword(s):  
Image Processing ◽  
Special Section ◽  
Biologically Inspired ◽  
Future Directions

scholarly journals Tracking the continuous dynamics of numerical processing: A brief review and editorial

2018 ◽  
Author(s):  
Thomas J. Faulkenberry ◽  
Matthias Witte ◽  
Matthias Hartmann
Keyword(s):  
Numerical Cognition ◽  
Mental Arithmetic ◽  
Special Section ◽  
Past Research ◽  
Number Processing ◽  
Hand Tracking ◽  
Single Digit ◽  
Future Directions ◽  
Numerical Processing ◽  
Computer Mouse

Many recent studies in numerical cognition have moved beyond the use of purely chronometric techniques in favor of methods which track the continuous dynamics of numerical processing. Two examples of such techniques include eye tracking and hand tracking (or computer mouse tracking). To reflect this increased concentration on continuous methods, we have collected a group of 5 articles that utilize these techniques to answer some contemporary questions in numerical cognition. In this editorial, we discuss the two paradigms and provide a brief review of some of the work in numerical cognition that has profited from the use of these techniques. For both methods, we discuss the past research through the frameworks of single digit number processing, multidigit number processing, and mental arithmetic processing. We conclude with a discussion of the papers that have been contributed to this special section and point to some possible future directions for researchers interested in tracking the continuous dynamics of numerical processing.

A SURVEY OF BIOLOGICALLY INSPIRED IMAGE PROCESSING FOR OBJECTS RECOGNITION

2009 ◽  
Vol 09 (04) ◽  
pp. 495-510 ◽  
Author(s):  
WEIREN SHI ◽  
ZUOJIN LI ◽  
XIN SHI ◽  
ZHI ZHONG
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Vision System ◽  
Human Vision ◽  
Image Perception ◽  
Biologically Inspired ◽  
Recognition Mechanism ◽  
Environmental Objects ◽  
Future Work ◽  
Animal Vision

The human vision system is a very sophisticated image processing and objects recognition mechanism. However, it is a challenge to simulate the human or animal vision system to automate visual function in machines, because it is difficult to account for the view-invariant perception of universals such as environmental objects or processes and the explicit perception of featural parts and wholes in visual scenes. In this paper, we first present an introduction to the importance of biologically inspired computer vision and review general and key vision functions from neuroscience perspective. And most significantly, we give an important summarization to and discussion on the specific applications of biologically inspired modeling, including biologically inspired image pre-processing, image perception, and objects recognition. In the end, we give some important and challenging topics of computer vision for future work.

scholarly journals Digitisation, Archiving, and Distribution of Photographic Data from Schmidt Surveys

1995 ◽  
Vol 148 ◽  
pp. 176-185
Author(s):  
Barry M. Lasker
Keyword(s):  
Image Processing ◽  
Future Directions ◽  
Use Of Data ◽  
Scan Data ◽  
Scanning Systems

AbstractThe limititations to the use of data from the major Schmidt surveys, i.e. grain noise as well as practical considerations of image processing and astrometry, are discussed, together with the question of mounting films on microdensitometer platens. Next, the major scanning systems dedicated to Schmidt surveys, their accomplishments, and their future programs are considered. Finally, the archiving and distribution of the scan data is discussed, and some suggestions regarding future directions are made.

scholarly journals Special Section on Pharmacogenomics: recent advances and future directions

2013 ◽  
Vol 58 (6) ◽  
pp. 305-305 ◽  
Author(s):  
Taisei Mushiroda ◽  
Kathleen M Giacomini ◽  
Michiaki Kubo
Keyword(s):  
Special Section ◽  
Future Directions ◽  
Recent Advances
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