Martin, N., Chevallet, J.-P., & Mulhem, P. (2025, October). Melanoma Segmentation with SAM-Like Models: Assessing the Influence and Limits of Bounding Box Input. Paper presented at CBMI 2025, Dublin, Ireland.

Martin, N., Chevallet, J.-P., & Mulhem, P. (2025, September). From Prediction to Prompt: Leveraging nnU-Net Outputs to Guide SAM for Active Learning in 3D Dental Segmentation. Paper presented at MICCAI 2025, ODIN Workshop, Daejeon, South Korea.

Cojean, S., Galuscakova, P., & Martin, N. (2025, July). Beyond Interpolation: Enhancing Large Language Models (LLMs) with Mental Models. Paper presented at CogSci 2025, San Francisco, USA.

Cojean, S. & Martin, N. (2025). Outils intégrant de l’intelligence artificielle pour l’éducation : quelles opportunités pour quelles limites ?. La Revue de Santé Scolaire et Universitaire.

Martin, N., Chevallet, J.-P., Mulhem, P., & Quénot, G. (2025, March). Active Learning for melanoma segmentation: Integration of human annotation and segmentation model predictions. Paper presented at IABM 2025, Nice, France.

Martin, N., Chevallet, J.-P., Mulhem, P., & Quénot, G. (2024, September). Combining Image and Region Uncertainty-based Active learning for Melanoma Segmentation. Paper presented at CBMI 2024, Reykjavik, Iceland.

Martin, N., Chevallet, J.-P., Mulhem, P., & Quénot, G. (2024, March). Toward Semantically Enriched Dental Diagnostics: Combination of Segmentation and Transformer Networks. Paper presented at IABM 2024, Grenoble, France.

Martin, N., Chevallet, J.-P., Mulhem, P., & Quénot, G. (2024, January). Vers la combinaison de modèles de segmentation et transformers pour la détection des maladies dentaires. Paper presented at EGC 2023, Dijon, France.

Cojean, S., Grand, M., & Martin, N. (2023, July). Note-taking during and after class: which strategies for which method?. Paper presented at COGSCI 2023, Sydney, Australia.

Martin, N., Chevallet, J.-P., & Quénot, G. (2022, September). Segmenting partially annotated medical images. Paper presented at CBMI 2022, Graz, Austria.

Cojean, S., & Martin, N. (2022, July). Adaptive Learning Technology based on Working Memory Capacity. Paper presented at COGSCI 2022, Toronto, Canada.

Cojean, S., & Martin, N. (2022, July). Acceptability of technology involving artificial intelligence among future teachers. Paper presented at COGSCI 2022, Toronto, Canada.

Luong, T., Lécuyer, A., Martin, N., & Argelaguet, F. (2021). A Survey on Affective and Cognitive VR. IEEE Transactions on Visualization and Computer Graphics

Cojean, S., & Martin, N. (2021). Reducing the split-attention effect of subtitles during video learning: might the use of occasional keywords be an effective solution? Topics in Cognitive Psychology.

Martin, N., Ragot, M., & Savaux, V. (2021, May). Acceptability and 5G in the Medical Field: The Impact of the Level of Information. Paper presented at ZINC 2021, Novi Sad, Serbia.

Terrier, R.* & Martin, N.* (2020, November). A machine learning tool to match 2D drawings and 3D objects' category for populating mockups in VR. Paper presented at EuroVR 2020.

Luong, T.*, Martin, N.*, Raison, A., Diverrez, J-M. Argelaguet, F. & Lécuyer, A. (2020, November). Towards Real-Time Recognition of Users’ Mental Workload in VR Using Integrated Physiological Sensors in a Custom HMD. Paper presented at ISMAR 2020.

Martin, N., Mathieu, N., Pallamin, N., Ragot, M. & Diverrez, J-M. (2020, November). Virtual reality sickness recognition: an approach based on physiological signals and machine learning. Paper presented at ISMAR 2020.

Terrier, R., Martin, N., Lacoche, J., Gouranton, V. & Arnaldi, B. (2020). Do distant or co-located audiences affect user activity in VR? Transactions on Computational Science.

Ragot, M., Martin, N., & Michaud--Redon, C. (2020, July). Effect of semantics terms on public perception of Artificial Intelligence. Paper presented at COGSCI 2020, Toronto, Canada.

Martin, N., Cojean, S., & Ragot, M. (2020, July). The Acceptability of AI at Work: Predicting the Intention to Use relying on UTAUT. Paper presented at COGSCI 2020, Toronto, Canada.

Cojean, S., Martin, N., & Ragot, M. (2020, July). What is the influence of the type of scale on score? A study on Likert and Visual Analogue Scale. Paper presented at COGSCI 2020, Toronto, Canada.

Ragot, M., Martin, N., & Cojean, S. (2020, April). AI-generated vs. human artworks. A perception bias towards Artificial Intelligence?. Paper presented at CHI 2020, Honolulu, USA.

Luong, T., Argelaguet, F., Martin, N., & Lécuyer, A. (2020, March). Introducing Mental Workload Measures for the Design of Virtual Reality Training Scenarios. Paper presented at IEEE VR 2020, Atlanta, USA.

Lecuyer, G., Ragot, M., Martin, N., Launay, L. & Jannin, P. (2020). Assisted phase and step annotation for surgical videos. International Journal of Computer Assisted Radiology and Surgery.

Terrier, R., Martin, N., Lacoche, J., Gouranton, V. & Arnaldi, B. (2019, Juin). Am I better in VR with a real audience?. Paper presented at the CGI, Calgary, Canada.

Lecuyer, G., Ragot, M., Martin, N., Launay, L. & Jannin, P. (2019, Juin). Assisted Annotation of Surgical Videos Using Deep Learning. Paper presented at the CARS, Rennes, France.

Luong, T., Martin, N., Argelaguet, F. & Lécuyer, A. (2019, Mars). Studying the Mental Effort in Virtual Versus Real Environments. Paper presented at the IEEE VR, Osaka, Japan.

Martin, N., Diverrez, J-M., Em, S., Pallamin, N. & Ragot, M. (2019) How to Recognize Emotions Without Signal Processing. In Neuroergonomics (p. 191-194). Elsevier.

Martin, N., Mathieu, N., Pallamin, N., Ragot, M. & Diverrez, J-M. (2018, September). Automatic recognition of Virtual Reality sickness based on Physiological Signal. Paper presented at the International Broadcasting Convention (IBC), Amsterdam, Netherlands.

Pallamin, N., Martin, N., Ragot, M., Diverrez, J-M. & Jégou, G. (2017, September). Automatic detection of VR sickness based on Machine Learning. Paper presented at the International Broadcasting Convention (IBC), Amsterdam, Netherlands.

Ragot, M., Martin, N., Em, S., Pallamin, N. & Diverrez, J-M. (2017, July).  Emotion recognition using physiological signals: laboratory vs. wearable sensors. In Ahram T., Falcão C. (eds). Advances in Human Factors in Wearable Technologies and Game Design. Paper presented at the International Conference on Applied Human Factors and Ergonomics (AHFE): Los Angeles, USA (pp. 15-22). Advances in Intelligent Systems and Computing, vol 608. Springer, Cham.

Diverrez, J-M., Martin, N., Ragot, M., Pallamin, N. & Em, S. (2017, July). Virtual reality, a new way to elicit emotion in laboratory. Paper presented at the International Conference on Applied Human Factors and Ergonomics (AHFE), Los Angeles, USA.

Martin, N., Jamet, E., Erhel, S., & Rouxel, G. (2016, October). Evaluation of technological products in mobility context: first steps toward new scales with single items. In Proceedings of the 28th Conference on l'Interaction Homme-Machine. Paper presented at the Interaction Homme-Machine conference (IHM): Fribourg, Suisse (pp. 237-245). ACM.

Martin, N., Diverrez, J-M., Em, S., Pallamin, N. & Ragot, M. (2016, October). How to recognize emotion without signal processing: an application of convolutional neural network to physiological signals. Paper presented at Neuroergonomics, Paris, France.

Martin, N., Diverrez, J-M. (2016, July).  From Physiological Measures to an Automatic Recognition System of Stress. In Stephanidis C. (eds). HCI International 2016 – Posters' Extended Abstracts. Paper presented at the Human-Computer Interaction International conference (HCII): Toronto, Canada (pp. 172-176). Communications in Computer and Information Science, vol 618. Springer, Cham.

Martin, N., Jamet E., Erhel S., Rouxel G. (2016, July).  From Acceptability to Acceptance: Does Experience with the Product Influence User Initial Representations?. In Stephanidis C. (eds). HCI International 2016 – Posters' Extended Abstracts. Paper presented at the Human-Computer Interaction International conference (HCII): Toronto, Canada (pp. 172-176). Communications in Computer and Information Science, vol 617. Springer, Cham.

Diverrez, J-M., Martin, N. & Pallamin, N. (2016, May). Stress interface inducer, a way to generate stress in laboratory conditions. Paper presented at the Measuring Behavior conference, Dublin, Ireland.

Martin, N., Erhel, S., Jamet, E., & Rouxel, G. (2015, October). Quels liens entre acceptabilité et expérience utilisateur ?. In Proceedings of the 27th Conference on l'Interaction Homme-Machine Paper presented at the Interaction Homme-Machine conference (IHM): Toulouse, France (pp. 34-39). ACM.