HYBRID EVENT: You Can Participate In Person At Adana, Turkey Or Virtually From Your Home Or Work
ICCVML · Registering as Listener

International Conference on Computer Vision and Machine Learning

4–5 Dec 2026 Adana, Turkey Standard / Physical Participation
Listener Registration
$135
virtual · $175 in person
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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  • If any concerns regarding authorship arise and are validated, the paper will be withdrawn without reconsideration.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 [email protected] 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 [email protected].
  • 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.

8. Conference Programme and Participation Policy :

  • Presentations from different but relevant academic areas may be combined by the Organiser within an interdisciplinary or multidisciplinary programme to encourage cross-disciplinary understanding, interaction, and future research partnerships.
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What you'll hear about

Session tracks covered across the event.
View all 11 tracks →
This track focuses on the latest developments in convolutional neural networks (CNNs) for computer vision applications. Researchers are invited to present novel architectures, optimization techniques, and performance evaluations of CNNs in various domains.
This session will explore cutting-edge methods for image recognition and classification, emphasizing the role of machine learning algorithms. Contributions that highlight real-world applications and comparative studies are particularly encouraged.
This track aims to discuss state-of-the-art object detection techniques, including both traditional and deep learning approaches. Papers that address challenges in real-time detection and applications in autonomous systems are welcome.
This session will delve into advanced feature extraction and selection methodologies crucial for enhancing machine learning performance. Contributions that propose innovative techniques or frameworks for feature engineering are highly sought after.
This track will cover the latest segmentation algorithms, focusing on their applications in various fields such as medical imaging and autonomous driving. Researchers are encouraged to present novel approaches and comparative analyses of segmentation techniques.
This session will focus on methodologies for video analysis, including motion detection, tracking, and event recognition. Contributions that explore the integration of machine learning with video processing are particularly encouraged.
This track will address innovative approaches to anomaly detection in visual data, highlighting the importance of machine learning in identifying outliers. Papers that discuss applications in security, healthcare, and industrial monitoring are welcome.
This session will explore deep learning architectures specifically designed for visual analytics, emphasizing interpretability and usability. Researchers are invited to present frameworks that bridge the gap between deep learning and practical analytics.
This track will focus on the application of transfer learning techniques in computer vision tasks, discussing both theoretical and practical implications. Contributions that demonstrate successful case studies or novel methodologies are encouraged.
This session will explore the use of unsupervised and reinforcement learning in computer vision applications, emphasizing innovative algorithms and their effectiveness. Papers that present empirical results or theoretical advancements are welcome.
This track will delve into the intersection of pattern recognition and visual perception, focusing on how machine learning can enhance understanding of visual data. Contributions that explore cognitive aspects and computational models are particularly encouraged.