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ICIPML · Registering as Listener
International Conference on Image Processing with Machine Learning
17–18 Aug 2026
Florence, Italy
Standard / Physical
Participation
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$
169
virtual · $246 in person
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Certificate & digital materials
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Supporting global research
Connect with researchers across 30+ countries
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Standard / Physical
$246
On-site keynotes, talks, workshops, networking, conference kit and certificate.
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$169
Live streaming access to all sessions, digital materials and certificate.
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Standard Registration Closed
The deadline for Standard Participation has ended. Participants may continue with Virtual Registration to join the conference remotely.
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1. Policy on Cancellations & Refunds :
A full refund is possible only if the cancellation request is submitted at least 70 days before the conference, with formal paperwork completed at least 60 days prior.
If cancellation occurs between 60 and 30 days before the event, partial refunds may be granted based on administrative costs incurred.
Cancellations made within 30 days of the event are non-refundable, though participants will receive a credit valid for one year.
Registrations made less than 30 days before the event are not eligible for refunds, but may be transferred to another ISIT conference.
Since this conference is hybrid format, the organizer reserves the right to conduct the event either in-person or virtually. Please note that no refunds will be issued due to changes in the event format.
Virtual registration fees are non-refundable. A credit will instead be issued for use at a future conference event.
2. Participation & Registration Requirements :
To attend an ISIT event, participants must complete the registration process within the stipulated time.
The event schedule, venue, and format are subject to changes at the discretion of the organizers, with prior notice sent via email.
ISIT is not liable for any financial losses resulting from changes in event details.
Fees paid for registration are strictly non-refundable.
If the primary author cannot participate, a co-author may attend instead, but refunds will not be granted for non-attendance.
3. Submission & Publication Norms :
Researchers submitting papers to ISIT must ensure their institution or supervisor is aware of their submission.
Each submission is subject to a rigorous peer review before being accepted for presentation.
Only papers linked to a completed registration will be included in conference proceedings.
The submitting author is considered the primary author; ISIT does not verify individual authorship claims.
If any concerns regarding authorship arise and are validated, the paper will be withdrawn without reconsideration.
Once a paper is removed, it cannot be reintroduced into any ISIT publication.
4. Travel & Accommodation Responsibilities :
Attendees are responsible for making their own travel and lodging arrangements.
ISIT does not provide logistical assistance for travel or accommodation.
The organization bears no responsibility for expenses incurred due to conference modifications or rescheduling.
5. Visa & Invitation Letter Policy :
Attendees are responsible for making their own travel and lodging arrangements.
ISIT does not provide logistical assistance for travel or accommodation.
The organization bears no responsibility for expenses incurred due to conference modifications or rescheduling.
ISIT does not engage directly with consulates or embassies on behalf of attendees.
Participants must handle their own visa applications and processes.
Important Information Regarding Invitation Letters:
The invitation letter is provided solely for conference attendance and does not serve as a document for immigration, employment, or residency purposes.
The letter assists in visa applications but does not guarantee visa approval.
ISIT holds no responsibility for visa denials or processing delays, and all related costs are borne by the applicant.
Any alterations or unauthorized use of the invitation letter will result in its invalidation and possible cancellation of conference participation.
Legal action may be pursued if the document is misused.
By accepting the invitation letter, attendees agree to comply with international travel regulations and ethical participation standards.
6. Registration Transfers :
Registrations may be transferred to another individual from the same institution if the original participant cannot attend.
Transfer requests must be made via email to info@isit.org.in with necessary details and supporting documents.
Transfers must be requested at least 14 days before the event; otherwise, they will not be accommodated.
Transferred registrations are not eligible for refunds.
7. General Considerations :
Any modifications or cancellations must be communicated in writing to info@isit.org.in.
Registration confirms acknowledgment and acceptance of these policies.
ISIT does not initiate automatic transactions; all payments are voluntarily completed by registrants.
Once registered, participants must submit a conference registration form within three days for confirmation.
Travel plans should only be finalized after receiving the official conference itinerary, which will be shared 15 days before the event.
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What you'll hear about
Session tracks covered across the event.
View all 11 tracks →
01
Advancements in Image Enhancement Techniques
This track focuses on the latest methodologies and algorithms for improving image quality through machine learning. Participants will explore novel approaches to enhance visual clarity and detail in various imaging modalities.
02
Object Detection and Recognition in Complex Environments
This session delves into cutting-edge techniques for detecting and recognizing objects within intricate scenes using machine learning. Emphasis will be placed on real-time applications and the challenges posed by occlusions and varying lighting conditions.
03
Segmentation Algorithms for Medical Imaging
This track highlights innovative segmentation algorithms specifically tailored for medical imaging applications. Researchers will present their findings on improving diagnostic accuracy through precise delineation of anatomical structures.
04
Feature Extraction Techniques for Image Analysis
This session will cover advanced feature extraction methods that enhance the performance of image classification tasks. Participants will discuss the implications of these techniques on various machine learning models.
05
Pattern Recognition in Visual Data
This track examines the latest developments in pattern recognition methodologies applied to visual data. The focus will be on algorithms that facilitate the identification of complex patterns in diverse datasets.
06
Deep Learning Architectures for Image Classification
This session is dedicated to exploring state-of-the-art deep learning architectures for image classification tasks. Researchers will share insights on optimizing neural networks for improved accuracy and efficiency.
07
Predictive Modeling in Image Processing
This track investigates the role of predictive modeling techniques in enhancing image processing applications. Discussions will include the integration of machine learning models to forecast outcomes based on visual data.
08
Image Denoising Techniques Using Machine Learning
This session focuses on innovative machine learning approaches for image denoising. Participants will explore various algorithms that effectively reduce noise while preserving essential image features.
09
Video Analysis and Understanding
This track addresses the challenges and advancements in video analysis through machine learning techniques. Researchers will present methods for action recognition, tracking, and scene understanding in dynamic environments.
10
Facial Recognition Technologies and Applications
This session will cover the latest advancements in facial recognition technologies powered by machine learning. Discussions will include ethical considerations and the impact of these technologies on privacy and security.
11
Transfer Learning and Its Applications in Image Processing
This track explores the concept of transfer learning and its effectiveness in various image processing tasks. Participants will discuss case studies demonstrating the successful application of pre-trained models in new domains.