Analysis Of Interest Points Of Curvelet Coefficients Contributions Of Microscopic Images And Improvement Of Edges - A. Djimeli; Daniel Tchiotsop; René Tchinda (CoRR, 2013)

Edge detection of intestinal parasites in stool microscopic images using multi-scale wavelet transform. - Daniel Tchiotsop; Beaudelaire Saha Tchinda; René Tchinda; Godpromesse Kenné (Signal Image Video Process., 2015)

Denoising of electroencephalographic signals by canonical correlation analysis and by second-order blind source separation. - Yris Brice Wandji Piugie; Daniel Tchiotsop; Adelaïde Nicole Kengnou Telem; Elie Bertrand Megam Ngouonkadi (AFRICON, 2019)

EEG signals analysis for epileptic seizures detection using polynomial transforms, linear discriminant analysis and support vector machines. - Laurent Chanel Djoufack Nkengfack; Daniel Tchiotsop; Romain Atangana; Valérie Louis-Dorr; Didier Wolf (Biomed. Signal Process. Control., 2020)

An accurate unsupervised extraction of retinal vasculature using curvelet transform and classical morphological operators. - Feudjio Ghislain; Beaudelaire Saha Tchinda; Daniel Tchiotsop (Comput. Biol. Medicine, 2024)

An improved deep learning approach for automated detection of multiclass eye diseases. - Feudjio Ghislain; Beaudelaire Saha Tchinda; Romain Atangana; Daniel Tchiotsop (Array, 2025)

Retinal vasculature extraction algorithm based on an improved and lightweight U-Net deep learning model using the dense block. - Beaudelaire Saha Tchinda; Zidane Rigasse Tchoupou Segning; Daniel Tchiotsop; René Tchinda (Multim. Tools Appl., 2025)