Workshop website: https://trustvis-bmvc2026.github.io/
Dr Guangliang Cheng, Dr Zeyu Fu, Dr Jianbo Jiao, Prof Xiaowei Huang
on behalf of the TrustVis Organising Committee
August 25th, 2026
Daniela Lopez de Luise
August 25th, 2026
Daniela Lopez de Luise We invite you to submit a paper and/or participate in the 4th AAAI Fall Symposium on Unifying Representations for Robot Application Development (UR-RAD). UR-RAD 2026 will be an in-person event.
Capturing a desired task or interaction as a computational artifact (i.e., a representation) has long played a pivotal role in robotics. Many robotic subfields have traditionally employed a variety of different representational techniques, such as LTL, planning languages, social representations, natural language, and many more. These representations, however, lack cohesion in when and how they are applied. The 4th Symposium on Unifying Representations for Robot Application Development (UR-RAD) therefore aims to increase engagement between junior and senior researchers, elevate discussion between audiences and speakers, and provide unique avenues of interaction for all participants.
Symposium Website: ur-rad.github.io
AAAI Fall Symposium Series Website: https://aaai.org/conference/fall-symposia/2026-fall-symposium-series-2/
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We invite the following contributions, formatted using the
AAAI-26 Author Kit: ===================
Organizing Committee
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David Porfirio (George Mason University)
August 25th, 2026
Daniela Lopez de Luise For anyone studying computer vision and medical image analysis, applying deep learning to dental radiography presents distinct challenges in feature extraction and anatomical localization.
Dental radiographs often feature dense, overlapping structures, low contrast margins, and significant variation across imaging hardware. Manual landmark identification remains labor-intensive and susceptible to inter-observer variability. This tutorial utilizes YOLOv8 as a single-stage detector because it delivers high mean Average Precision (mAP) on closely packed, low-contrast bounding boxes while maintaining real-time inference speeds suitable for practical clinical pipelines and batch processing.
Detailed written explanation and source code: https://eranfeit.net/how-to-build-yolov8-dental-object-detection-model/
The end-to-end workflow begins by establishing an isolated PyTorch environment with CUDA acceleration. The dataset is structured into normalized YOLO-format annotations paired with a custom dataset configuration file. Before initiating model training, normalized bounding box coordinates are converted to pixel dimensions and rendered using OpenCV to verify annotation alignment against raw X-ray data. Once validated, the YOLOv8 architecture is trained on GPU, and the resulting weights are evaluated by comparing predicted bounding boxes against ground-truth annotations in a side-by-side visual analysis.
Reading on Medium: https://medium.com/object-detection-tutorials/how-to-build-yolov8-dental-object-detection-model-07ee6ee36296
Join my Newsletter : https://eranfeit.net/advance-your-skills-in-computer-vision-ai/
Deep-dive video walkthrough: https://youtu.be/mfv1ps-tHDk
This content is intended for educational purposes only. Constructive feedback, technical questions, and discussions regarding custom dataset training or model optimization are welcome in the comments.
Enjoy,
Eran
August 25th, 2026
Daniela Lopez de Luise FG 2027 marks an important milestone in the history of the conference series, as IEEE FG will be held in Africa for the first time.
Special Sessions provide an opportunity to highlight focused, emerging, and interdisciplinary research topics within the broader scope of face and gesture recognition, modeling, and analysis. Special Sessions are fully integrated into the main conference program. Papers submitted to Special Sessions will undergo the same rigorous peer-review process as regular submissions and, if accepted, will be included in the conference proceedings.
We particularly encourage proposals addressing emerging research directions, novel application domains, new challenges, and interdisciplinary topics that can bring new perspectives to the FG community.
Proposals should be sent to the FG 2027 Special Session Chairs, Benjamin Riggan and Aparna Bharti, at:
Full details and submission guidelines are available on the FG 2027 website:
https://fg2027.ieee-biometrics.org/call-for-special-session-proposals-2/
We look forward to receiving your proposals and welcoming you to Marrakesh for FG 2027.
Best regards,
IEEE FG 2027 Organizing Committee
August 25th, 2026
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