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ORCIDKumar T. Rajamani
Person information
- affiliation: University of Lübeck, Germany
- affiliation: Robert Bosch Engineering & Solutions Ltd., Bangalore, India
- affiliation (PhD): University of Bern, Switzerland
Other persons with the same name
- Kumar Rajamani 0002 — Marwadi Education Foundation's Group of Institutions, Gujarat, India
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Journal Articles
- 2023
[j10]Srividya Tirunellai Rajamani
, Kumar T. Rajamani, Ashwin Venkateshvaran, Andreas Triantafyllopoulos, Alexander Kathan, Björn W. Schuller:
Toward Detecting and Addressing Corner Cases in Deep Learning Based Medical Image Segmentation. IEEE Access 11: 95334-95345 (2023)- [j9]Kumar T. Rajamani, Priya Rani, Hanna Siebert, Elagiri Ramalingam Rajkumar, Mattias P. Heinrich:
Attention-augmented U-Net (AA-U-Net) for semantic segmentation. Signal Image Video Process. 17(4): 981-989 (2023) - 2022
- [j8]Pullalarevu Karthik, Mansi Parashar, S. Sofana Reka, Kumar T. Rajamani, Mattias P. Heinrich:
Semantic segmentation for plant phenotyping using advanced deep learning pipelines. Multim. Tools Appl. 81(3): 4535-4547 (2022) - [j7]C. C. Benson, V. L. Lajish, Kumar Rajamani:
Classification of Low-Grade and High-Grade Glioma from MR Brain Images Using Multiple-Instance Learning with Combined Feature Set. Vietnam. J. Comput. Sci. 9(2): 163-186 (2022) - 2021
- [j6]Kumar T. Rajamani, Hanna Siebert, Mattias P. Heinrich:
Dynamic deformable attention network (DDANet) for COVID-19 lesions semantic segmentation. J. Biomed. Informatics 119: 103816 (2021) - 2018
- [j5]K. Gayathri Devi, R. Radhakrishnan, Kumar T. Rajamani:
Segmentation of colon and removal of opacified fluid for virtual colonoscopy. Pattern Anal. Appl. 21(1): 205-219 (2018) - 2016
- [j4]Selvakumar Karuppusamy, Jovitha Jerome, Kumar Rajamani:
Robust face identification using DTCWT and PCA subspace based sparse representation. Multim. Tools Appl. 75(23): 16073-16092 (2016) - [j3]Selvakumar Karuppusamy, Jovitha Jerome, Kumar T. Rajamani, Nishanth Shankar:
Real-Time Vision Based Driver Drowsiness Detection Using Partial Least Squares Analysis. J. Signal Process. Syst. 85(2): 263-274 (2016) - 2007
- [j2]Kumar T. Rajamani, Martin Andreas Styner, Haydar Talib, Guoyan Zheng, Lutz-Peter Nolte, Miguel Ángel González Ballester:
Statistical deformable bone models for robust 3D surface extrapolation from sparse data. Medical Image Anal. 11(2): 99-109 (2007) - [j1]Guoyan Zheng, Xiao Dong, Kumar T. Rajamani, Xuan Zhang, Martin Styner, Ramesh U. Thoranaghatte, Lutz-Peter Nolte, Miguel Ángel González Ballester:
Accurate and Robust Reconstruction of a Surface Model of the Proximal Femur From Sparse-Point Data and a Dense-Point Distribution Model for Surgical Navigation. IEEE Trans. Biomed. Eng. 54(12): 2109-2122 (2007)
Conference and Workshop Papers
- 2023
- [c31]Srividya Tirunellai Rajamani, Kumar T. Rajamani, Björn W. Schuller:
A novel and simple approach to regularise attention frameworks and its efficacy in segmentation. EMBC 2023: 1-4 - 2022
- [c30]Gouthamaan Manimaran, Urmila Airsang, Soumabha Bhowmick, Abhijith Girin, Luoluo Liu, Carol Lane, Dheepak S, Celine Firtion, Pallavi Vajinepalli, Kumar Thirunellai Rajamani:
Evaluation Tool to Diagnose Faults and Discrepancy in Semi-Automated or Manual Annotations in Ultrasound Cine Loops (Videos). EMBC 2022: 525-528 - [c29]Srividya Tirunellai Rajamani, Kumar Rajamani, Priya Rani, Rashmita Barick, Ramasubramanya M. S, Sridevi V. Aithal, Elagiri Ramalingam Rajkumar, Sahana D. Gowda, Björn W. Schuller:
Novel no-reference multi-dimensional perceptual similarity metric. EMBC 2022: 2045-2048 - [c28]Srividya Tirunellai Rajamani, Kumar Rajamani, Alexander Kathan, Björn W. Schuller:
Novel Insights on Induced Sparsity in Multi-Time Attention Networks. EMBC 2022: 2615-2618 - [c27]Kumar Rajamani, Sahana D. Gowda, Vishwa Nedunoori Tej, Srividya Tirunellai Rajamani:
Deformable attention (DANet) for semantic image segmentation. EMBC 2022: 3781-3784 - 2021
- [c26]Srividya Tirunellai Rajamani, Kumar T. Rajamani, Adria Mallol-Ragolta, Shuo Liu, Björn W. Schuller:
A Novel Attention-Based Gated Recurrent Unit and its Efficacy in Speech Emotion Recognition. ICASSP 2021: 6294-6298 - [c25]Prateek Gupta, Hanna Siebert, Mattias P. Heinrich, Kumar T. Rajamani:
DA-AR-Net: an attentive activation based Deformable auto-encoder for group-wise registration. Medical Imaging: Image Processing 2021 - [c24]Hanna Siebert, Kumar T. Rajamani, Mattias P. Heinrich:
Learning inverse consistent 3D groupwise registration with deforming autoencoders. Medical Imaging: Image Processing 2021 - [c23]Srividya Tirunellai Rajamani, Kumar T. Rajamani, Björn W. Schuller:
Towards an Efficient Deep Learning Model for Emotion and Theme Recognition in Music. MMSP 2021: 1-5 - 2020
- [c22]Srividya Tirunellai Rajamani, Kumar T. Rajamani, Björn W. Schuller:
Emotion and Theme Recognition in Music Using Attention-Based Methods. MediaEval 2020 - 2017
- [c21]Bhavani Sambaturu, Bhargav Srinivasan, Sahana Muraleedhara Prabhu, Kumar Thirunellai Rajamani, Thennarasu Palanisamy, Girish Haritz, Digvijay Singh:
A novel deep learning based method for retinal lesion detection. ICACCI 2017: 33-37 - [c20]C. C. Benson, V. L. Lajish, Kumar T. Rajamani:
Robust classification of MR brain images based on fractal dimension analysis. ICACCI 2017: 1135-1140 - [c19]I. Syed Muhammedh Ajwahir, Kumar T. Rajamani, S. Ibrahim Sadhar:
A Novel Technique for Splat Generation and Patch Level Prediction in Diabetic Retinopathy. MIUA 2017: 50-59 - 2016
- [c18]Melih Kandemir, Manuel Haußmann, Ferran Diego, Kumar T. Rajamani, Jeroen van der Laak, Fred A. Hamprecht:
Variational Weakly Supervised Gaussian Processes. BMVC 2016 - [c17]Matthias von Borstel, Melih Kandemir, Philip Schmidt, Madhavi K. Rao, Kumar T. Rajamani, Fred A. Hamprecht:
Gaussian Process Density Counting from Weak Supervision. ECCV (1) 2016: 365-380 - [c16]C. C. Benson, V. Deepa, V. L. Lajish, Kumar T. Rajamani:
Brain tumor segmentation from MR brain images using improved fuzzy c-means clustering and watershed algorithm. ICACCI 2016: 187-192 - [c15]R. Santhakumar, Elagiri Ramalingam Rajkumar, Megha Tandur, K. S. Geetha, Kumar Thirunellai Rajamani, Girish Haritz:
A fast algorithm for optic disc segmentation in fundus images. ICACCI 2016: 716-719 - [c14]Amruthavarshini, Kavya Venkatesan, K. S. Geetha, Digvijay Singh, Kumar T. Rajamani:
Multiple instance learning for the determination of appropriate images for fundus image algorithms. ICACCI 2016: 727-730 - 2015
- [c13]Benson C. C., Lajish V. L., Kumar T. Rajamani:
Brain tumor extraction from MRI brain images using marker based watershed algorithm. ICACCI 2015: 318-323 - [c12]Priya Rani, Elagiri Ramalingam Rajkumar, Kumar T. Rajamani, Melih Kandemir, Digvijay Singh:
Detection of Retinopathy of Prematurity using multiple instance learning. ICACCI 2015: 2233-2237 - 2014
- [c11]Sai Vignesh T, Siva Subramaniyan V, Kumar T. Rajamani, Siva Sankara Sai S:
An interactive GUI tool for thyroid Uptake studies using Gamma Camera. ICACCI 2014: 305-309 - 2012
- [c10]Kumar Rajamani, Dattesh D. Shanbhag, Rakesh Mullick, Sohan Ranjan, Uday Patil, Sandeep N. Gupta:
Detection of abrupt motion in DCE-MRI. Medical Imaging: Image Processing 2012: 83144J - 2011
- [c9]V. Naveen Kumar, Mrigank Rochan, Santosh Hariharan, Kumar Rajamani:
Data hiding scheme for medical images using lossless code for mobile HIMS. COMSNETS 2011: 1-4 - 2006
- [c8]Guoyan Zheng, Kumar T. Rajamani, Lutz-Peter Nolte:
Use of a Dense Surface Point Distribution Model in a Three-Stage Anatomical Shape Reconstruction from Sparse Information for Computer Assisted Orthopaedic Surgery: A Preliminary Study. ACCV (2) 2006: 52-60 - [c7]Haydar Talib, Kumar T. Rajamani, Jens Kowal, Martin Styner, Miguel Ángel González Ballester:
Assessing the feasibility of ultrasound-initialized deformable bone models. Medical Imaging: Image-Guided Procedures 2006: 61410R - [c6]Guoyan Zheng, Kumar T. Rajamani:
An optimal three-stage method for anatomical shape reconstruction from sparse information using a dense surface point distribution model. Medical Imaging: Image-Guided Procedures 2006: 614110 - 2005
- [c5]Kumar T. Rajamani, Miguel Ángel González Ballester, Lutz-Peter Nolte, Martin Styner:
A novel and stable approach to anatomical structure morphing for enhanced intraoperative 3D visualization. Medical Imaging: Image-Guided Procedures 2005 - 2004
- [c4]Kumar T. Rajamani, Martin Styner, Sarang C. Joshi:
Bone Model Morphing for Enhanced Surgical Visualization. ISBI 2004: 1255-1258 - [c3]Kumar T. Rajamani, Lutz-Peter Nolte, Martin Styner:
A Novel Approach to Anatomical Structure Morphing for Intraoperative Visualization. MICCAI (2) 2004: 478-485 - [c2]Kumar T. Rajamani, Johannes Hug, Lutz-Peter Nolte, Martin Styner:
Bone morphing with statistical shape models for enhanced visualization. Medical Imaging: Image-Guided Procedures 2004 - 2003
- [c1]Martin Styner, Kumar T. Rajamani, Lutz-Peter Nolte, Gabriel Zsemlye, Gábor Székely, Christopher J. Taylor, Rhodri H. Davies:
Evaluation of 3D Correspondence Methods for Model Building. IPMI 2003: 63-75
Coauthor Index
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