Welcome to IPMV 2021
2021 3rd International Conference on Image Processing and
Machine Vision will be held in Hong Kong on May 22-24, 2021.
Image Processing and Machine Vision usually
plays an important role in the transition from data storage
to decision systems based on large databases of signals
such as the obtained from sensor networks, internet
services, or communication systems. These systems imply
developing both computational solutions and novel models.
Signals from real-world systems are usually complex such as
speech, music, bio-medical, multimedia, among others. Thus,
Image Processing and Machine Vision techniques are very
useful for these type of systems to automate processing and
analysis techniques to retrieve information from data
IPMV 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 will put
special emphasis on the participations of PhD students,
Postdoctoral fellows and other young researchers from all
over the world. It would be beneficial to bring together a
group of experts from diverse fields to discuss recent
progress and to share ideas on open questions.
You are invited to submit a paper for consideration all over the globe interested in the areas of
machine learning methods/ algorithms, signal processing
theory and methods, data mining, artificial intelligence,
optimization and applications to human brain disorders like
epilepsy etc. Other applications of image processing and
machine vision techniques are also welcome. Looking forward to welcoming you in Hong Kong!
Submitted papers will be peer-reviewed by
technical program committees based on the paper's topic,
quality, etc. Accepted and presented papers will be
published into Conference Proceedings, which will
be submitted and reviewed by Ei Compendex and Scopus
Index. Welcome you to submit your full paper or
Electronic Submission System.
IPMV 2020 Conference Proceedings丨ACM (ISBN: 978-1-4503-8841-2)