IPCV'20 - The 24th Int'l Conf on Image Processing, Computer Vision, & Pattern Recognition

by admin last modified Jan 19, 2020 05:14 PM

IPCV is an international conference that serves researchers, scholars, professionals, students, and academicians who are looking to both foster working relationships and gain access to the latest research results. It is being held jointly (same location and dates) with a number of other research conferences; namely, The 2020 World Congress in Computer Science, Computer Engineering, and Applied Computing (CSCE'20).

We anticipate having between 1,000 and 2,000 participants in the Congress. The congress includes 20 major tracks composed of: 122 technical, research, and panel sessions as well as a number of keynote lectures and tutorials; all will be held simultaneously, same location and dates: July 27-30, 2020. Last year, the Congress had attracted speakers/authors and participants affiliated with over 158 different universities (including many from the top 50 ranked institutions), major IT corporations (including: Microsoft, Google, Apple, SAP, Facebook, Oracle, Amazon, Yahoo, Samsung, IBM, Ebay, GE, Siemens, Philips, Ericsson, BAE Systems, Hitachi, NTT, Twitter, Uber Technologies, ...), major corporations (including: Exxon Mobil, Johnson & Johnson, JPMorgan Chase, PetroChina, GlaxoSmithKline, HSBC, Airbus, Boeing, Hyundai, Goldman Sachs, Deutsche Bank, ...), government research agencies (NSF, NIH, DoE, US Air Force, NSA National Security Agency, Central Intelligence Agency, ...), US national laboratories (including, NASA National Aeronautics and Space Administration, ANL Argonne National Lab, Sandia National Lab, ORNL Oak Ridge National Lab, Lawrence Berkeley National Lab, Lawrence Livermore National Lab, Los Alamos National Lab, Pacific Northwest National Lab, ...), and a number of Venture Capitalists as well as distinguished speakers discussing Intellectual Property issues. Last year, 54% of attendees were from academia, 25% from industry; 20% from government and funding agencies; and 1% unknown. About half of the attendees were from outside USA; from 69 nations.

The primary goal of this conference is to provide a platform for researchers, scientists, industry experts and scholars to share their novel ideas and research results on the application of human cognition models in various practical computing applications. Through this conference, the organizers would like to develop an interdisciplinary venue to contribute and discuss the ongoing innovations, applications and solutions to challenging problems of engineering human brain processes, learning mechanisms and decision making processes.

You are invited to submit a paper for consideration. ALL ACCEPTED PAPERS will be published in the corresponding proceedings by Publisher: Springer Nature - Book Series: Transactions on Computational Science & Computational Intelligence https://www.springer.com/series/11769

Indexation: Subject to Springer science indexation which includes: online Springer Link (link.springer.com/), Scopus (www.info.scopus.com), SCI Compendex, EI Compendex (www.ei.org), EMBASE, Web of Science, Inspec, ACM digital library, Google Scholar, EBSCO, and others. Prospective authors are invited to submit their papers by uploading them to the evaluation web site at:  https://american-cse.org/

Prologue:

The broad area of Imaging Science is a field that is mainly concerned with the generation, collection, analysis, modification, and visualization of images. The field is multidisciplinary in that it includes topics that are traditionally covered in computer science, physics, mathematics, electrical engineering, AI, psychology and information theory where computer science acts as the topical bridge between all such diverse areas (for a formal definition of Imaging Science, refer to relevant wiki pages.) From the computer science perspective, the core of Imaging Science includes the following three intertwined computer science fields, namely: Image Processing, Computer Vision, and Pattern Recognition. This conference will cover the research trends in these three important areas.

The list of topics of interest that appears below is not meant to be exhaustive.

    • IMAGE PROCESSING:

(Addresses ow-level processing as well as imaging fundamentals.)

- Software Tools for Imaging
- Image Generation, Acquisition, and Processing
- Image-based Modeling and Algorithms
- Mathematical Morphology
- Image Geometry and Multi-view Geometry
- 3D Imaging
- Novel Noise Reduction Algorithms
- Image Restoration
- Enhancement Techniques
- Segmentation Techniques
- Motion and Tracking Algorithms and Applications
- Watermarking Methods and Protection + Wavelet Methods
- Image Data Structures and Databases
- Image Compression, Coding, and Encryption
- Video Analysis
- Multi-resolution Imaging Techniques
- Performance Analysis and Evaluation
- Multimedia Systems and Applications
- Novel Image Processing Applications

  • COMPUTER VISION:

(Addresses mid- to high-level processing as well as vision fundamentals.) 

- Camera Networks and Vision
- Sensors and Early Vision
- Machine Learning Technologies for Vision
- Image Feature Extraction
- Cognitive and Biologically Inspired Vision
- Object Recognition
- Soft Computing Methods in Image Processing and Vision
- Stereo Vision
- Active and Robot Vision
- Face and Gesture Recognition
- Fuzzy and Neural Techniques in Vision
- Medical Image Processing and Analysis
- Novel Document Image Understanding Techniques
- Special-purpose Machine Architectures for Vision
- Biometric Authentication
- Novel Vision Application and Case Studies

    • PATTERN RECOGNITION:

(Addresses pattern recognition algorithms and methodologies that are of value to the image processing and computer vision research communities.) 

- Supervised and Un-supervised Classification Algorithms
- Clustering Techniques
- Dimensionality Reduction Methods in Pattern Recognition
- Symbolic Learning
- Ensemble Learning Algorithms
- Parsing Algorithms
- Bayesian Methods in Pattern Recognition and Matching
- Statistical Pattern Recognition
- Invariance in Pattern Recognition
- Knowledge-based Recognition
- Structural and Syntactic Pattern Recognition
- Applications Including: Security, Medicine, Robotic, GIS, Remote Sensing, Industrial Inspection, Nondestructive Evaluation (or NDE), ... 
- Case studies and Emerging technologies

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