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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
About me
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Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
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Blog Post number 2
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Blog Post number 1
Published:
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portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
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publications
Mental State Prediction by Deployment of Trained SVM Model on EEG Brain Signal
Published in 2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS), 2018
Bidur Khanal, Satish Pant, Kushal Pokharel, Susan Gaire. Mental State Prediction by Deployment of Trained SVM Model on EEG Brain Signal. In 2018 IEEE 3rd International Conference on Computing Communication and Security (ICCCS). IEEE, 2018. [Oral Presentation]
Automatic Cobb Angle Detection using Vertebra Detector and Vertebra Corners Regression
Published in Computational Methods and Clinical Applications for Spine Imaging, 2020
Bidur Khanal, Lavsen Dahal, Prashant Adhikari, Bishesh Khanal.Automatic Cobb Angle Detection using Vertebra Detector and Vertebra Corners Regression. In MICCAI 2019 Challenge on Accurate Automated Spinal Curvature Estimation & Workshop on Computational Methods and Clinical Applications for Spine Imaging [ Oral Presentation]
Evaluation and comparison of accurate automated spinal curvature estimation algorithms with spinal anterior-posterior X-Ray images: The AASCE2019 challenge
Published in Medical Image Analysis, 2021
Liansheng Wang, Cong Xie, Yi Lin, Hong-Yu Zhou, Kailin Chen, Dalong Cheng, Florian Dubost, Benjamin Collery, Bidur Khanal et al. “Evaluation and comparison of accurate automated spinal curvature estimation algorithms with spinal anterior-posterior X-Ray images: The AASCE2019 challenge.” Medical Image Analysis 72 (2021): 102115.
How Does Heterogeneous Label Noise Impact Generalization in Neural Nets?
Published in International Symposium on Visual Computing, 2021
Bidur Khanal, and Christopher Kanan. How Does Heterogeneous Label Noise Impact Generalization in Neural Nets? In International Symposium on Visual Computing, pp. 229-241. Springer, Cham, 2021.
Machine-Learning-Assisted Analysis of Colorimetric Assays on Paper Analytical Devices
Published in American Chemical Society (ACS) omega, 2021
Bidur Khanal, Pravin Pokhrel, Bishesh Khanal, Basant Giri. “Machine-Learning-Assisted Analysis of Colorimetric Assays on Paper Analytical Devices”. ACS omega 6, no. 49 (2021): 33837-33845
Label Geometry Aware Discriminator for Conditional Generative Networks.
Published in International Association of Pattern Recognition (ICPR), 2022
Sapkota, Suman, Bidur Khanal, Binod Bhattarai, Bishesh Khanal, and Tae-Kyun Kim. “Label Geometry Aware Discriminator for Conditional GAN.” In 26TH International Conference on Pattern Recognition. 2022.
Investigating the impact of class-dependent label noise in medical image classification
Published in SPIE Medical Imaging, 2023
Bidur Khanal, SM Kamrul Hasan, Bishesh Khanal, and Cristian A. Linte. “Investigating the impact of class-dependent label noise in medical image classification.” In Medical Imaging 2023: Image Processing, vol. 12464, pp. 728-733. SPIE, 2023.
M-VAAL: Multimodal Variational Adversarial Active Learning for Downstream Medical Image Analysis Tasks
Published in Medical Image Understanding and Analysis (MIUA), 2023
Bidur Khanal, Binod Bhattarai, Bishesh Khanal, Danail Stoyanov, and Cristian A. Linte. “M-VAAL: Multimodal Variational Adversarial Active Learning for Downstream Medical Image Analysis Tasks.” Medical Image Understanding and Analysis (MIUA), 2023. [Oral Presentation]
Improving Medical Image Classification in Noisy Labels Using only Self-supervised Pretraining
Published in MICCAI Workshop on Data Engineering in Medical Imaging (DEMI), 2023
Bidur Khanal, Binod Bhattarai, Bishesh Khanal, and Cristian A. Linte. “Improving Medical Image Classification in Noisy Labels Using only Self-supervised Pretraining.” In MICCAI Workshop on Data Engineering in Medical Imaging, pp. 78-90. Cham: Springer Nature Switzerland, 2023.
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.