Revues avec comité de lecture

 

  1. Quyet Tien Le, Patricia Ladret, Huu-Tuan Nguyen, Alice Caplier « Computational Analysis of correlations between Image Aesthetic and Image Naturalness in the relation with image quality” . J. Imaging 2022, 8(6), 166; https://doi.org/10.3390/jimaging8060166.
  2. D. Urban, A. Caplier "Time and Resource Efficient Time to collision forecasting for indoor pedestrian obstacles avoidance" Journal of Imaging, 2021, 7, 61, https://www.mdpi.com/2313-433X/7/4/61
  3. Quyet Tien Le, Patricia Ladret, Huu-Tuan Nguyen, Alice Caplier. Study of naturalness in tone-mapped images. Computer Vision and Image Understanding, Elsevier, 2020, 196, pp.102971. ⟨ 10.1016/j.cviu.2020.102971
  4. D. Al Chanti, A. Caplier – « Deep learning for spatio temporal modeling of dynamic spontaneous emotions » IEEE Trans on Affective Computing, DOI: 10.1109/TAFFC.2018.2873600, oct 2018.
  5. T. Edmunds, A. Caplier – Face Spoofing based on colour distorsions – IET Biometrics, Special Issue Face recognition and Spoofing Attacks, Volume 7, Issue 1, January 2018, p. 27 – 38.
  6. T. Edmunds, A. Caplier « Motion-based countermeasure against photo and video spoofing attacks in face recognition” Journal of Visual Communication and Image Representation 50 (2018) 314–332

 Conférences internationales

 

  1. P-A Afro, L. Struc, L. Bonnaud, A. Caplier, F. Robin “Rate Distorsion Optimized Quantization Using Deep Learning” IEEE Int. Conf on Visual Communications and Image Processing, Korea, Dec 2023.  
  2. M. Urard, C. Paquet, C. Beylier, J.N Pena, A. Caplier, M. Dalla Maura, R. Bange, R. Guizetti « Training Dataset Optimization for Deep Learning applied to Optical Proximity Correction on non-regular hole masks “ Proc EMLC 2023 - 38th European Mask and Lithography Conference, Dresden, Germany, June 2023.
  3. S. Gholipour, D. AL Chanti, A. Caplier « How far generated data can impact neural netwroks performances?” In VISAPP Conference, Lisbon, Portugal, February 2023.
  4. Alfred Laugros, Alice Caplier, Matthieu Ospici. “Using Synthetic Corruptions to Measure Robustness to Natural Distribution Shifts”, in BMVC, November 2021.
  5. Alfred Laugros, Alice Caplier, Matthieu Ospici. “Using the overlapping score to imrove corruption benchmarks”, In ICIP, Anchorage, Alaska, USA, September 2021
  6. Alfred Laugros, Alice Caplier, Matthieu Ospici. Addressing Neural Network Robustness with Mixup and Targeted Labeling Adversarial Training. ECCV RLQ Workshop, Aug 2020, Glasgow, United Kingdom. ⟨hal-02925252⟩
  7. Alfred Laugros, Alice Caplier, Matthieu Ospici. Are Adversarial Robustness and Common Perturbation Robustness Independent Attributes? ICCV 2019 - International Conference on Computer Vision, Oct 2019, Seoul, South Korea.
  8. Quyet Tien Le, Patricia Ladret, Huu-Tuan Nguyen, Alice Caplier. Large Field/Close-Up Image Classification: From Simple to Very Complex Features. Mario Vento; Gennaro Percannella. Computer Analysis of Images and Patterns, 11679, Springer, pp.532-543, 2019, Lecture Notes in Computer Science, 978-3-030-29890-6
  9. M. Garcia, A. Caplier, M. Rombault “Sleep deprivation detection for real time driver monitoring using deep learning” ICIAR, Portugal, June 2018
  10. D. Al Chanti, A. Caplier “Improving bag of visual words towards effective facial expressive image classification” Proc of VISIGRAPH, Madeira, Portugal, Jan 2018.
  11. D. Al Chanti, A. Caplier “Spontaneous Facial Expression Recognition using Sparse Representation” Proc. of the 12th International Conference on Computer Vision Theory and Applications, VISAPP, Porto, Portugal, February 2017.