Patrice Monkam

Orcid: 0000-0003-3805-9457

According to our database1, Patrice Monkam authored at least 15 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
An Attention-Based Deep Learning Network for Predicting Platinum Resistance in Ovarian Cancer.
IEEE Access, 2024

2023
LVSnake: Accurate and robust left ventricle contour localization for myocardial infarction detection.
Biomed. Signal Process. Control., August, 2023

Annotation Cost Minimization for Ultrasound Image Segmentation Using Cross-Domain Transfer Learning.
IEEE J. Biomed. Health Informatics, April, 2023

An attention-based deep learning network for predicting Platinum resistance in ovarian cancer.
CoRR, 2023

US-Net: A lightweight network for simultaneous speckle suppression and texture enhancement in ultrasound images.
Comput. Biol. Medicine, 2023

2022
Super-Resolution of Seismic Velocity Model Guided by Seismic Data.
IEEE Trans. Geosci. Remote. Sens., 2022

EMRNet: End-to-End Electrical Model Restoration Network.
IEEE Trans. Geosci. Remote. Sens., 2022

An efficient annotated data generation method for echocardiographic image segmentation.
Comput. Biol. Medicine, 2022

Deep Neural Network-Based Noisy Pixel Estimation for Breast Ultrasound Segmentation.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

2021
Multitask Learning for Super-Resolution of Seismic Velocity Model.
IEEE Trans. Geosci. Remote. Sens., 2021

Seismic Structural Curvature Volume Extraction With Convolutional Neural Networks.
IEEE Trans. Geosci. Remote. Sens., 2021

EasySpec: Automatic Specular Reflection Detection and Suppression From Endoscopic Images.
IEEE Trans. Computational Imaging, 2021

2019
Ensemble Learners of Multiple Deep CNNs for Pulmonary Nodules Classification Using CT Images.
IEEE Access, 2019

Ensemble Learning of Multiple-View 3D-CNNs Model for Micro-Nodules Identification in CT Images.
IEEE Access, 2019

Detection and Classification of Pulmonary Nodules Using Convolutional Neural Networks: A Survey.
IEEE Access, 2019


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