Call for Special Sessions
The MLSP 2021 technical program will highlight a series of Special Sessions to complement the regular program with important and emerging topics in a field of special interest to the MLSP participants. Each Special Session should be a focused effort rather than defined broadly.
Special Session Requirements
The target for each Special Session is more than 5 accepted papers (minimum 4 papers). The following information should be included in the proposal:
- Title of the proposed special session.
- Names and affiliations of the organizers (including brief bio and contact info).
- Session abstract (state the motivation and significance of the topic, and the rationale of the proposed session).
- List of invited papers (including a tentative title, author list and a 300-word abstract for each paper).
In addition to invited papers, other potential authors will be allowed to submit papers to Special Sessions. All papers will go through the same review process as the regular papers submitted to the main conference to ensure that the contributions are of high quality.
Proposals will be evaluated based on the timeliness of the topic and relevance to MLSP, as well as the track record of the organizers and anticipated quality of papers in the proposal session. When considering submitting a Special Session proposal, please bear in mind that approved Special Session organizer(s) and Special Session Chairs are expected to coordinate the review process.
For further inquiries you may contact the organizers at: email@example.com.
- Special Session Proposals Due: April 30th, 2021
- Notification of Special Session Acceptance: May 7th, 2021
- Submission of full-length papers: May 31st, 2021
- Special Session Proposal: Submission Form Template – PDF Format
- Special Session Proposal: Submission Form Template – Word Format
Proposals should be submitted to firstname.lastname@example.org before the deadline.
Accepted Special Sessions
The following special sessions have been accepted.
- Machine Learning for Image and Video Understanding,
- Prof. Xinxiao Wu, Beijing Institute of Technology, China
- Prof. Han Wang, Beijing Forestry University, China
- Real-time vision-based contactless perception for human-centered smart building and human health,
- Prof. Xiaogang CHENG, Nanjing University of Posts and Telecommunications, China
- Prof. Bin Yang, Xi’ An University of Architecture and Technology, China