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ORCIDTapabrata Chakraborti
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2020 – today
- 2024
[j14]Zhan Shen
, Tapabrata Chakraborti, Wenyan Wang, Shuaiting Yao, Zhizhong Fu, Yifan Chen, Xiaorong Ding:
Uncertainty quantification of cuffless blood pressure estimation based on parameterized model evidential ensemble learning. Biomed. Signal Process. Control. 92: 106104 (2024)- [j13]Liangyi Lyu, Lei Lu, Hanjie Chen, David A. Clifton, Yuanting Zhang, Tapabrata Chakraborti:
An improved deep regression model with state space reconstruction for continuous blood pressure estimation. Comput. Electr. Eng. 118: 109319 (2024) - [j12]Alistair Knott, Dino Pedreschi, Toshiya Jitsuzumi, Susan Leavy, David M. Eyers, Tapabrata Chakraborti, Andrew Trotman, Sundar Sundareswaran, Ricardo Baeza-Yates, Przemyslaw Biecek, Adrian Weller, Paul D. Teal, Subhadip Basu, Mehmet Haklidir, Virginia Morini, Stuart Russell, Yoshua Bengio:
AI content detection in the emerging information ecosystem: new obligations for media and tech companies. Ethics Inf. Technol. 26(4): 63 (2024) - [j11]Alistair Knott, Dino Pedreschi, Toshiya Jitsuzumi, Susan Leavy, David M. Eyers, Tapabrata Chakraborti, Andrew Trotman, Sundar Sundareswaran, Ricardo Baeza-Yates, Przemyslaw Biecek, Adrian Weller, Paul D. Teal, Subhadip Basu, Mehmet Haklidir, Virginia Morini, Stuart Russell, Yoshua Bengio:
Correction: AI content detection in the emerging information ecosystem: new obligations for media and tech companies. Ethics Inf. Technol. 26(4): 71 (2024) - [c20]Faizanuddin Ansari, Tapabrata Chakraborti, Swagatam Das:
Algorithmic Fairness in Lesion Classification by Mitigating Class Imbalance and Skin Tone Bias. MICCAI (1) 2024: 373-382 - [c19]Zhihang Ren, Yunqi Li, Xinyu Li, Xinrong Xie, Erik P. Duhaime, Kathy Fang, Tapabrata Chakraborti, Yunhui Guo, Stella X. Yu, David Whitney:
SkinCON: Towards Consensus for the Uncertainty of Skin Cancer Sub-typing Through Distribution Regularized Adaptive Predictive Sets (DRAPS). MICCAI (1) 2024: 405-415 - [c18]Avigyan Bhattacharya, Tapabrata Chakraborti, Subhadip Basu, Alistair Knott, Dino Pedreschi, Raja G. Chatila, Susan Leavy, David M. Eyers, Paul D. Teal, Przemyslaw Biecek:
Towards a crowdsourced framework for online hate speech moderation - a case study in the Indian political scenario. WebSci (Companion) 2024: 75-84 - [i8]Anthony Baptista, Alessandro Barp, Tapabrata Chakraborti, Chris Harbron, Ben D. MacArthur, Christopher R. S. Banerji:
Deep Learning as Ricci Flow. CoRR abs/2404.14265 (2024) - 2023
- [j10]Brijesh Kumar Sriwastava, Anup Kumar Halder, Subhadip Basu, Tapabrata Chakraborti:
RUBic: rapid unsupervised biclustering. BMC Bioinform. 24(1): 435 (2023) - [j9]Alistair Knott, Dino Pedreschi, Raja Chatila, Tapabrata Chakraborti, Susan Leavy, Ricardo Baeza-Yates, David M. Eyers, Andrew Trotman, Paul D. Teal, Przemyslaw Biecek, Stuart Russell, Yoshua Bengio:
Generative AI models should include detection mechanisms as a condition for public release. Ethics Inf. Technol. 25(4): 55 (2023) - [j8]Robin Mitra, Sarah F. McGough, Tapabrata Chakraborti, Chris C. Holmes, Ryan Copping, Niels Hagenbuch, Stefanie Biedermann, Jack Noonan, Brieuc Lehmann, Aditi Shenvi, Xuan Vinh Doan, David Leslie, Ginestra Bianconi, Rubén J. Sánchez-García, Alisha Davies, Maxine Mackintosh, Eleni-Rosalina Andrinopoulou, Anahid Basiri, Chris Harbron, Ben D. MacArthur:
Learning from data with structured missingness. Nat. Mac. Intell. 5(1): 13-23 (2023) - [c17]Samiran Dey, Tapabrata Chakraborti, Partha Basuchowdhuri, Debasis Mitra, Robin Augustine, Sanjoy Kumar Saha:
MoMSGAN: Mode Collapse based Degradation Agnostic Multi-Scale Super-Resolution of Medical Images. ICVGIP 2023: 14:1-14:9 - [c16]Samiran Dey, Partha Basuchowdhuri, Debasis Mitra, Robin Augustine, Sanjoy Kumar Saha, Tapabrata Chakraborti:
BliMSR: Blind Degradation Modelling for Generating High-Resolution Medical Images. MIUA 2023: 64-78 - [i7]Robin Mitra, Sarah F. McGough, Tapabrata Chakraborti, Chris C. Holmes, Ryan Copping, Niels Hagenbuch, Stefanie Biedermann, Jack Noonan, Brieuc Lehmann, Aditi Shenvi, Xuan Vinh Doan, David Leslie, Ginestra Bianconi, Rubén J. Sánchez-García, Alisha Davies, Maxine Mackintosh, Eleni-Rosalina Andrinopoulou, Anahid Basiri, Chris Harbron, Ben D. MacArthur:
Learning from data with structured missingness. CoRR abs/2304.01429 (2023) - 2022
- [j7]Kunal Biswas, Palaiahnakote Shivakumara, Umapada Pal, Tapabrata Chakraborti, Tong Lu, Mohamad Nizam Bin Ayub:
Fuzzy and genetic algorithm based approach for classification of personality traits oriented social media images. Knowl. Based Syst. 241: 108024 (2022) - [c15]George Batchkala, Tapabrata Chakraborti, Mark McCole, Fergus Gleeson, Jens Rittscher:
Active Data Enrichment by Learning What to Annotate in Digital Pathology. CaPTion@MICCAI 2022: 118-127 - 2021
- [c14]Sebastian Elmes, Tapabrata Chakraborti, Mengran Fan, Holm H. Uhlig, Jens Rittscher:
Automated Annotator: Capturing Expert Knowledge for Free. EMBC 2021: 2664-2667 - [c13]Helen Theissen, Tapabrata Chakraborti, Stefano Malacrino, Korsuk Sirinukunwattana, Daniel Royston, Jens Rittscher:
Learning Cellular Phenotypes through Supervision. EMBC 2021: 3592-3595 - [c12]Tapabrata Chakraborti, Fergus Gleeson, Jens Rittscher:
Contrastive Representations for Continual Learning of Fine-Grained Histology Images. MLMI@MICCAI 2021: 1-9 - [c11]Tamal Chowdhury, Angad R. S. Bajwa, Tapabrata Chakraborti, Jens Rittscher, Umapada Pal:
Exploring the Correlation Between Deep Learned and Clinical Features in Melanoma Detection. MIUA 2021: 3-17 - 2020
- [c10]Arijit Patra, Tapabrata Chakraborti:
Learn More, Forget Less: Cues from Human Brain. ACCV (4) 2020: 187-202 - [c9]Mengran Fan, Tapabrata Chakraborti, Eric I-Chao Chang, Yan Xu, Jens Rittscher:
Fine-Grained Multi-Instance Classification in Microscopy Through Deep Attention. ISBI 2020: 169-173 - [c8]Tapabrata Chakraborti, Brendan McCane, Steven Mills, Umapada Pal:
CoCoNet: A Collaborative Convolutional Network applied to fine-grained bird species classification. IVCNZ 2020: 1-6 - [c7]Tapabrata Chakraborti, Brendan McCane, Steven Mills, Umapada Pal:
PProCRC: Probabilistic Collaboration of Image Patches for Fine-grained Classification. IVCNZ 2020: 1-5 - [c6]Jia Sun, Tapabrata Chakraborti, J. Alison Noble:
A Comparative Study of Explainer Modules Applied to Automated Skin Lesion Classification. XI-ML@KI 2020 - [c5]Mengran Fan, Tapabrata Chakraborti, Eric I-Chao Chang, Yan Xu, Jens Rittscher:
Microscopic Fine-Grained Instance Classification Through Deep Attention. MICCAI (5) 2020: 490-499 - [i6]Mengran Fan, Tapabrata Chakraborti, Eric I-Chao Chang, Yan Xu, Jens Rittscher:
Microscopic fine-grained instance classification through deep attention. CoRR abs/2010.02818 (2020)
2010 – 2019
- 2019
- [j6]Rukhmini Roy, Tapabrata Chakraborti, Ananda S. Chowdhury:
A deep learning-shape driven level set synergism for pulmonary nodule segmentation. Pattern Recognit. Lett. 123: 31-38 (2019) - [i5]Tapabrata Chakraborti, Brendan McCane, Steven Mills, Umapada Pal:
CoCoNet: A Collaborative Convolutional Network. CoRR abs/1901.09886 (2019) - [i4]Tapabrata Chakraborti, Brendan McCane, Steven Mills, Umapada Pal:
PProCRC: Probabilistic Collaboration of Image Patches. CoRR abs/1903.09123 (2019) - [i3]Tapabrata Chakraborti, Brendan McCane, Steven Mills, Umapada Pal:
Distance Metric Learned Collaborative Representation Classifier. CoRR abs/1905.01168 (2019) - [i2]Tapabrata Chakraborti, Arijit Patra, J. Alison Noble:
Contrastive Algorithmic Fairness: Part 1 (Theory). CoRR abs/1905.07360 (2019) - 2018
- [j5]Tapabrata Chakraborti, Brendan McCane, Steven Mills, Umapada Pal:
LOOP Descriptor: Local Optimal-Oriented Pattern. IEEE Signal Process. Lett. 25(5): 635-639 (2018) - [c4]Tapabrata Chakraborti, Brendan McCane, Steven Mills, Umapada Pal:
Fine-grained Collaborative K-Means Clustering. IVCNZ 2018: 1-6 - 2017
- [c3]Tapabrata Chakraborti, Brendan McCane, Steven Mills, Umapada Pal:
A Generalised Formulation for Collaborative Representation of Image Patches (GP-CRC). BMVC 2017 - [i1]Tapabrata Chakraborti, Brendan McCane, Steven Mills, Umapada Pal:
LOOP Descriptor: Encoding Repeated Local Patterns for Fine-grained Visual Identification of Lepidoptera. CoRR abs/1710.09317 (2017) - 2016
- [c2]Nilamadhaba Tripathy, Tapabrata Chakraborti, Mita Nasipuri, Umapada Pal:
A scale and rotation invariant scheme for multi-oriented Character Recognition. ICPR 2016: 4041-4046 - [c1]Tapabrata Chakraborti, Brendan McCane, Steven Mills, Umapada Pal:
Collaborative representation based fine-grained species recognition. IVCNZ 2016: 1-6 - 2015
- [j4]Tapabrata Chakraborti, Amitava Chatterjee, Anisha Halder, Amit Konar:
Automated emotion recognition employing a novel modified binary quantum-behaved gravitational search algorithm with differential mutation. Expert Syst. J. Knowl. Eng. 32(4): 522-530 (2015) - [j3]Tapabrata Chakraborti, Dhiraj K. Jha, Ananda S. Chowdhury, Xiaoyi Jiang:
A self-adaptive matched filter for retinal blood vessel detection. Mach. Vis. Appl. 26(1): 55-68 (2015) - 2014
- [j2]Tapabrata Chakraborti, Amitava Chatterjee:
A novel binary adaptive weight GSA based feature selection for face recognition using local gradient patterns, modified census transform, and local binary patterns. Eng. Appl. Artif. Intell. 33: 80-90 (2014) - [j1]Tapabrata Chakraborti, Kaushik Das Sharma, Amitava Chatterjee:
A novel local extrema based gravitational search algorithm and its application in face recognition using one training image per class. Eng. Appl. Artif. Intell. 34: 13-22 (2014)
Coauthor Index
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