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2020 – today
- 2024
[j19]Philippe Weitz
, Masi Valkonen, Leslie Solorzano, Circe Carr, Kimmo Kartasalo, Constance Boissin, Sonja Koivukoski, Aino Kuusela, Dusan Rasic, Yanbo Feng, Sandra Kristiane Sinius Pouplier, Abhinav Sharma, Kajsa Ledesma Eriksson, Stephanie Robertson, Christian Marzahl, Chandler D. Gatenbee, Alexander R. A. Anderson, Marek Wodzinski, Artur Jurgas, Niccolò Marini, Manfredo Atzori, Henning Müller, Daniel Budelmann, Nick Weiss, Stefan Heldmann, Johannes Lotz, Jelmer M. Wolterink, Bruno De Santi, Abhijeet Patil, Amit Sethi, Satoshi Kondo, Satoshi Kasai, Kousuke Hirasawa, Mahtab Farrokh, Neeraj Kumar, Russell Greiner, Leena Latonen, Anne-Vibeke Laenkholm, Johan Hartman, Pekka Ruusuvuori, Mattias Rantalainen:
The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue. Medical Image Anal. 97: 103257 (2024)- [j18]Zhongao Sun, Alexander V. Khvostikov, Andrey S. Krylov, Amit Sethi, Ilya Mikhailov, Pavel Malkov:
Joint Super-resolution and Tissue Patch Classification for Whole Slide Histological Images. Program. Comput. Softw. 50(3): 257-263 (2024) - [c52]Ravi Kant Gupta, Shounak Das, Amit Sethi:
Unsupervised Domain Adaptation for Medical Images with an Improved Combination of Losses. BIOSTEC (1) 2024: 205-215 - [c51]Pranav Jeevan, Nikhil Cherian Kurian, Amit Sethi:
Magnification Invariant Medical Image Analysis: A Comparison of Convolutional Networks, Vision Transformers, and Token Mixers. BIOSTEC (1) 2024: 216-222 - [c50]Ardhendu Sekhar, Ravi Kant Gupta, Amit Sethi:
Few-Shot Histopathology Image Classification: Evaluating State-of-the-Art Methods and Unveiling Performance Insights. BIOSTEC (1) 2024: 244-253 - [c49]Amruta Parulekar, Utkarsh Kanwat, Ravi Kant Gupta, Medha Chippa, Thomas Jacob, Tripti Bameta, Swapnil Rane, Amit Sethi:
Combining Datasets with Different Label Sets for Improved Nucleus Segmentation and Classification. BIOSTEC (1) 2024: 281-288 - [c48]Sahar Almahfouz Nasser, Shashwat Pathak, Keshav Singhal, Mohit Meena, Nihar Gupte, Ananya Chinmaya, Prateek Garg, Amit Sethi:
Utilizing Radiomic Features for Automated MRI Keypoint Detection: Enhancing Graph Applications. BIOSTEC (1) 2024: 319-325 - [c47]Pranav Jeevan, Akella Srinidhi, Pasunuri Prathiba, Amit Sethi:
WaveMixSR: Resource-efficient Neural Network for Image Super-resolution. WACV 2024: 5872-5880 - [c46]Sahar Almahfouz Nasser, Nihar Gupte, Amit Sethi:
Reverse Knowledge Distillation: Training a Large Model using a Small One for Retinal Image Matching on Limited Data. WACV 2024: 7763-7772 - [i52]Pirzada Suhail, Supratik Chakraborty, Amit Sethi:
Network Inversion of Binarised Neural Nets. CoRR abs/2402.11995 (2024) - [i51]Akhila Krishna K, Ravi Kant Gupta, Pranav Jeevan, Amit Sethi:
Advancing Gene Selection in Oncology: A Fusion of Deep Learning and Sparsity for Precision Gene Selection. CoRR abs/2403.01927 (2024) - [i50]Shreyas Chandgothia, Ardhendu Sekhar, Amit Sethi:
IFSENet : Harnessing Sparse Iterations for Interactive Few-shot Segmentation Excellence. CoRR abs/2403.15089 (2024) - [i49]Pranav Jeevan, Amit Sethi:
Which Backbone to Use: A Resource-efficient Domain Specific Comparison for Computer Vision. CoRR abs/2406.05612 (2024) - [i48]Pirzada Suhail, Amit Sethi:
Network Inversion of Convolutional Neural Nets. CoRR abs/2407.18002 (2024) - [i47]Ardhendu Sekhar, Ravi Kant Gupta, Amit Sethi:
Few-Shot Histopathology Image Classification: Evaluating State-of-the-Art Methods and Unveiling Performance Insights. CoRR abs/2408.13816 (2024) - [i46]Ardhendu Sekhar, Vrinda Goel, Garima Jain, Abhijeet Patil, Ravi Kant Gupta, Amit Sethi:
HER2 and FISH Status Prediction in Breast Biopsy H&E-Stained Images Using Deep Learning. CoRR abs/2408.13818 (2024) - [i45]Pranav Jeevan, Neeraj Nixon, Amit Sethi:
WaveMixSR-V2: Enhancing Super-resolution with Higher Efficiency. CoRR abs/2409.10582 (2024) - [i44]Ashish Prasad, Pranav Jeevan, Amit Sethi:
EDSNet: Efficient-DSNet for Video Summarization. CoRR abs/2409.14724 (2024) - [i43]Sunny Gupta, Mohit Jindal, Pankhi Kashyap, Pranav Jeevan, Amit Sethi:
FLeNS: Federated Learning with Enhanced Nesterov-Newton Sketch. CoRR abs/2409.15216 (2024) - [i42]Abhijeet Patil, Harsh Diwakar, Jay Sawant, Nikhil Cherian Kurian, Subhash Yadav, Swapnil Rane, Tripti Bameta, Amit Sethi:
Efficient Quality Control of Whole Slide Pathology Images with Human-in-the-loop Training. CoRR abs/2409.19587 (2024) - [i41]Pranav Jeevan, Neeraj Nixon, Amit Sethi:
Normalizing Flow-Based Metric for Image Generation. CoRR abs/2410.02004 (2024) - 2023
- [c45]Nikhil Cherian Kurian, S. Varsha, Abhijit Patil, Shashikant Khade, Amit Sethi:
Robust Semi-Supervised Learning for Histopathology Images Through Self-Supervision Guided Out-of-Distribution Scoring. BIBE 2023: 121-128 - [c44]Tirupati Saketh Chandra, Sahar Almahfouz Nasser, Nikhil Cherian Kurian, Amit Sethi:
Improving Mitosis Detection via UNet-Based Adversarial Domain Homogenizer. BIOIMAGING 2023: 52-56 - [c43]Ravi Kant Gupta, Shivani Nandgaonkar, Nikhil Cherian Kurian, Tripti Bameta, Subhash Yadav, Rajiv Kumar Kaushal, Swapnil Rane, Amit Sethi:
EGFR Mutation Prediction of Lung Biopsy Images Using Deep Learning. BIOIMAGING 2023: 102-109 - [c42]Sahar Almahfouz Nasser, Amit Sethi:
Simulating Ultrasound Images from CT Scans. BIOIMAGING 2023: 138-145 - [c41]Dharshan Sampath Kumar, Pranav Jeevan, Amit Sethi:
Resource-efficient image inpainting. Tiny Papers @ ICLR 2023 - [c40]Akhila Krishna K, Ravi Kant Gupta, Nikhil Cherian Kurian, Pranav Jeevan, Amit Sethi:
Heterogeneous Graphs Model Spatial Relationship Between Biological Entities for Breast Cancer Diagnosis. GRAIL/OCELOT@MICCAI 2023: 97-106 - [i40]Pranav Jeevan, Nikhil Cherian Kurian, Amit Sethi:
Magnification Invariant Medical Image Analysis: A Comparison of Convolutional Networks, Vision Transformers, and Token Mixers. CoRR abs/2302.11488 (2023) - [i39]Nikhil Cherian Kurian, S. Varsha, Abhijit Patil, Shashikant Khade, Amit Sethi:
Robust Semi-Supervised Learning for Histopathology Images through Self-Supervision Guided Out-of-Distribution Scoring. CoRR abs/2303.09930 (2023) - [i38]Chirag P, Mukta Wagle, Ravi Kant Gupta, Pranav Jeevan, Amit Sethi:
CHATTY: Coupled Holistic Adversarial Transport Terms with Yield for Unsupervised Domain Adaptation. CoRR abs/2304.09623 (2023) - [i37]Philippe Weitz, Masi Valkonen, Leslie Solorzano, Circe Carr, Kimmo Kartasalo, Constance Boissin, Sonja Koivukoski, Aino Kuusela, Dusan Rasic, Yanbo Feng, Sandra Kristiane Sinius Pouplier, Abhinav Sharma, Kajsa Ledesma Eriksson, Stephanie Robertson, Christian Marzahl, Chandler D. Gatenbee, Alexander R. A. Anderson, Marek Wodzinski, Artur Jurgas, Niccolò Marini, Manfredo Atzori, Henning Müller, Daniel Budelmann, Nick Weiss, Stefan Heldmann, Johannes Lotz, Jelmer M. Wolterink, Bruno De Santi, Abhijeet Patil, Amit Sethi, Satoshi Kondo, Satoshi Kasai, Kousuke Hirasawa, Mahtab Farrokh, Neeraj Kumar, Russell Greiner, Leena Latonen, Anne-Vibeke Laenkholm, Johan Hartman, Pekka Ruusuvuori, Mattias Rantalainen:
The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue. CoRR abs/2305.18033 (2023) - [i36]Pranav Jeevan, Dharshan Sampath Kumar, Amit Sethi:
WavePaint: Resource-efficient Token-mixer for Self-supervised Inpainting. CoRR abs/2307.00407 (2023) - [i35]Pranav Jeevan, Akella Srinidhi, Pasunuri Prathiba, Amit Sethi:
WaveMixSR: A Resource-efficient Neural Network for Image Super-resolution. CoRR abs/2307.00430 (2023) - [i34]Akhila Krishna K, Ravi Kant Gupta, Nikhil Cherian Kurian, Pranav Jeevan, Amit Sethi:
Heterogeneous graphs model spatial relationships between biological entities for breast cancer diagnosis. CoRR abs/2307.08132 (2023) - [i33]Sahar Almahfouz Nasser, Nihar Gupte, Amit Sethi:
Reverse Knowledge Distillation: Training a Large Model using a Small One for Retinal Image Matching on Limited Data. CoRR abs/2307.10698 (2023) - [i32]Sahar Almahfouz Nasser, Ashutosh Sharma, Anmol Saraf, Amruta Mahendra Parulekar, Purvi Haria, Amit Sethi:
Transforming Breast Cancer Diagnosis: Towards Real-Time Ultrasound to Mammogram Conversion for Cost-Effective Diagnosis. CoRR abs/2308.05449 (2023) - [i31]Ravi Kant Gupta, Shounak Das, Amit Sethi:
Domain-Adaptive Learning: Unsupervised Adaptation for Histology Images with Improved Loss Function Combination. CoRR abs/2309.17172 (2023) - [i30]Amruta Parulekar, Utkarsh Kanwat, Ravi Kant Gupta, Medha Chippa, Thomas Jacob, Tripti Bameta, Swapnil Rane, Amit Sethi:
Combining Datasets with Different Label Sets for Improved Nucleus Segmentation and Classification. CoRR abs/2310.03346 (2023) - [i29]Sahar Almahfouz Nasser, Shashwat Pathak, Keshav Singhal, Mohit Meena, Nihar Gupte, Ananya Chinmaya, Prateek Garg, Amit Sethi:
Utilizing Radiomic Feature Analysis For Automated MRI Keypoint Detection: Enhancing Graph Applications. CoRR abs/2311.18281 (2023) - 2022
- [j17]Bibin Wilson, Anand Singh, Amit Sethi:
Appraisal of Resistivity Inversion Models With Convolutional Variational Encoder-Decoder Network. IEEE Trans. Geosci. Remote. Sens. 60: 1-10 (2022) - [j16]Ruchika Verma, Neeraj Kumar, Abhijeet Patil, Nikhil Cherian Kurian, Swapnil Rane, Amit Sethi:
Author's Reply to "MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge". IEEE Trans. Medical Imaging 41(4): 1000-1003 (2022) - [c39]Nikhil Cherian Kurian, Amit Lehan, Gregory Verghese, Nimish Dharamshi, Swati Meena, Mengyuan Li, Fangfang Liu, Cheryl Gillet, Swapnil Rane, Anita Grigoriadis, Amit Sethi:
Deep Multi-Scale U-Net Architecture and Label-Noise Robust Training Strategies for Histopathological Image Segmentation. BIBE 2022: 91-96 - [c38]Sahar Almahfouz Nasser, Nikhil Cherian Kurian, Mohit Meena, Saqib Shamsi, Amit Sethi:
WSSAMNet: Weakly Supervised Semantic Attentive Medical Image Registration Network. BrainLes@MICCAI (2) 2022: 15-24 - [c37]Sahar Almahfouz Nasser, Saqib Shamsi, Valay Bundele, Bhavesh Garg, Amit Sethi:
Perceptual cGAN for MRI Super-resolution. EMBC 2022: 3035-3038 - [c36]Bibin Wilson, Anand Singh, Amit Sethi:
Shallow Water Bathymetry Survey Using an Autonomous Surface Vehicle. IGARSS 2022: 7898-7901 - [c35]Nikhil Cherian Kurian, S. Varsha, Akshay Bajpai, Sunil Patel, Amit Sethi:
Improved Histology Image Classification under Label Noise Via Feature Aggregating Memory Banks. ISBI 2022: 1-5 - [c34]Pranav Jeevan, Amit Sethi:
Resource-efficient Hybrid X-formers for Vision. WACV 2022: 3555-3563 - [i28]Sahar Almahfouz Nasser, Saqib Shamsi, Valay Bundele, Bhavesh Garg, Amit Sethi:
Perceptual cGAN for MRI Super-resolution. CoRR abs/2201.09314 (2022) - [i27]Pranav Jeevan, Amit Sethi:
Convolutional Xformers for Vision. CoRR abs/2201.10271 (2022) - [i26]Pranav Jeevan, Amit Sethi:
WaveMix: Resource-efficient Token Mixing for Images. CoRR abs/2203.03689 (2022) - [i25]Sahar Almahfouz Nasser, Nikhil Cherian Kurian, Saqib Shamsi, Mohit Meena, Amit Sethi:
WSSAMNet: Weakly Supervised Semantic Attentive Medical Image Registration Network. CoRR abs/2203.07114 (2022) - [i24]Nikhil Cherian Kurian, Amit Lohan, Gregory Verghese, Nimish Dharamshi, Swati Meena, Mengyuan Li, Fangfang Liu, Cheryl Gillet, Swapnil Rane, Anita Grigoriadis, Amit Sethi:
Deep Multi-Scale U-Net Architecture and Noise-Robust Training Strategies for Histopathological Image Segmentation. CoRR abs/2205.01777 (2022) - [i23]Pranav Jeevan, Kavitha Viswanathan, Amit Sethi:
WaveMix-Lite: A Resource-efficient Neural Network for Image Analysis. CoRR abs/2205.14375 (2022) - [i22]Bibin Wilson, Rajiv Kumar, Narayanarao Bhogapurapu, Anand Singh, Amit Sethi:
Deriving Surface Resistivity from Polarimetric SAR Data Using Dual-Input UNet. CoRR abs/2207.01811 (2022) - [i21]Bibin Wilson, Anand Singh, Amit Sethi:
Shallow Water Bathymetry Survey using an Autonomous Surface Vehicle. CoRR abs/2207.08492 (2022) - [i20]Tirupati Saketh Chandra, Sahar Almahfouz Nasser, Nikhil Cherian Kurian, Amit Sethi:
Improving Mitosis Detection Via UNet-based Adversarial Domain Homogenizer. CoRR abs/2209.09193 (2022) - [i19]Harsh Shah, Thomas Jacob, Amruta Parulekar, Anjali Amarapurkar, Amit Sethi:
Artificial Intelligence-based Eosinophil Counting in Gastrointestinal Biopsies. CoRR abs/2211.15667 (2022) - 2021
- [j15]Ruchika Verma, Neeraj Kumar, Abhijeet Patil, Nikhil Cherian Kurian, Swapnil Rane, Simon Graham, Quoc Dang Vu, Mieke Zwager, Shan-E-Ahmed Raza, Nasir M. Rajpoot, Xiyi Wu, Huai Chen, Yijie Huang, Lisheng Wang, Hyun Jung, G. Thomas Brown, Yanling Liu, Shuolin Liu, Seyed Alireza Fatemi Jahromi, Ali Asghar Khani, Ehsan Montahaei, Mahdieh Soleymani Baghshah, Hamid Behroozi, Pavel Semkin, Alexandr Rassadin, Prasad Dutande, Romil Lodaya, Ujjwal Baid, Bhakti Baheti, Sanjay N. Talbar, Amirreza Mahbod, Rupert Ecker, Isabella Ellinger, Zhipeng Luo, Bin Dong, Zhengyu Xu, Yuehan Yao, Shuai Lv, Ming Feng, Kele Xu, Hasib Zunair, Abdessamad Ben Hamza, Steven M. Smiley, Tang-Kai Yin, Qi-Rui Fang, Shikhar Srivastava, Dwarikanath Mahapatra, Lubomira Trnavska, Hanyun Zhang, Priya Lakshmi Narayanan, Justin Law, Yinyin Yuan, Abhiroop Tejomay, Aditya Mitkari, Dinesh Koka, Vikas Ramachandra, Lata Kini, Amit Sethi:
MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge. IEEE Trans. Medical Imaging 40(12): 3413-3423 (2021) - [j14]Nikhil Cherian Kurian, Amit Sethi, Anil Reddy Konduru, Abhishek Mahajan, Swapnil Ulhas Rane:
A 2021 update on cancer image analytics with deep learning. WIREs Data Mining Knowl. Discov. 11(4) (2021) - [c33]Shubhang Bhatnagar, Sachin Goyal, Darshan Tank, Amit Sethi:
PAL : Pretext-based Active Learning. BMVC 2021: 195 - [c32]Nikhil Cherian Kurian, Gurparkash Singh, Poorvi Hebbar, Shreekanya Kodate, Swapnil Rane, Amit Sethi:
Robust Classification of Histology Images Exploiting Adversarial Auto Encoders. EMBC 2021: 2871-2874 - [c31]Abhijeet Patil, Mohd. Talha, Aniket Bhatia, Nikhil Cherian Kurian, Sammed Mangale, Sunil Patel, Amit Sethi:
Fast, Self Supervised, Fully Convolutional Color Normalization Of H&E Stained Images. ISBI 2021: 1563-1567 - [c30]Nikhil Cherian Kurian, Pragati Shuddhodhan Meshram, Abhijeet Patil, Sunil Patel, Amit Sethi:
Sample Specific Generalized Cross Entropy for Robust Histology Image Classification. ISBI 2021: 1934-1938 - [c29]Sahar Almahfouz Nasser, Nikhil Cherian Kurian, Amit Sethi:
Domain Generalisation for Mitosis Detection Exploting Preprocessing Homogenizers. MIDOG/MOOD/Learn2Reg@MICCAI 2021: 77-80 - [i18]Pranav Jeevan, Amit Sethi:
Vision Xformers: Efficient Attention for Image Classification. CoRR abs/2107.02239 (2021) - [i17]Himanshu Pradeep Aswani, Abhiraj Sunil Kanse, Shubhang Bhatnagar, Amit Sethi:
Memory Efficient Adaptive Attention For Multiple Domain Learning. CoRR abs/2110.10969 (2021) - 2020
- [j13]Neeraj Kumar, Ruchika Verma, Deepak Anand, Yanning Zhou, Omer Fahri Onder, Efstratios Tsougenis, Hao Chen, Pheng-Ann Heng, Jiahui Li, Zhiqiang Hu, Yunzhi Wang, Navid Alemi Koohbanani, Mostafa Jahanifar, Neda Zamani Tajeddin, Ali Gooya, Nasir M. Rajpoot, Xuhua Ren, Sihang Zhou, Qian Wang, Dinggang Shen, Cheng-Kun Yang, Chi-Hung Weng, Wei-Hsiang Yu, Chao-Yuan Yeh, Shuang Yang, Shuoyu Xu, Pak-Hei Yeung, Peng Sun, Amirreza Mahbod, Gerald Schaefer, Isabella Ellinger, Rupert Ecker, Örjan Smedby, Chunliang Wang, Benjamin Chidester, That-Vinh Ton, Minh-Triet Tran, Jian Ma, Minh N. Do, Simon Graham, Quoc Dang Vu, Jin Tae Kwak, Akshaykumar Gunda, Raviteja Chunduri, Corey Hu, Xiaoyang Zhou, Dariush Lotfi, Reza Safdari, Antanas Kascenas, Alison O'Neil, Dennis Eschweiler, Johannes Stegmaier, Yanping Cui, Baocai Yin, Kailin Chen, Xinmei Tian, Philipp Grüning, Erhardt Barth, Elad Arbel, Itay Remer, Amir Ben-Dor, Ekaterina Sirazitdinova, Matthias Kohl, Stefan Braunewell, Yuexiang Li, Xinpeng Xie, Linlin Shen, Jun Ma, Krishanu Das Baksi, Mohammad Azam Khan, Jaegul Choo, Adrián Colomer, Valery Naranjo, Linmin Pei, Khan M. Iftekharuddin, Kaushiki Roy, Debotosh Bhattacharjee, Aníbal Pedraza, Maria Gloria Bueno, Sabarinathan Devanathan, Saravanan Radhakrishnan, Praveen Koduganty, Zihan Wu, Guanyu Cai, Xiaojie Liu, Yuqin Wang, Amit Sethi:
A Multi-Organ Nucleus Segmentation Challenge. IEEE Trans. Medical Imaging 39(5): 1380-1391 (2020) - [c28]Mookund Sureka, Abhijeet Patil, Deepak Anand, Amit Sethi:
Visualization for Histopathology Images using Graph Convolutional Neural Networks. BIBE 2020: 331-335 - [c27]Bibin Wilson, Nikhil Cherian Kurian, Anand Singh, Amit Sethi:
Satellite-Derived Bathymetry Using Deep Convolutional Neural Network. IGARSS 2020: 2280-2283 - [c26]Deepak Anand, Darshan Tank, Harshvardhan Tibrewal, Amit Sethi:
Self-Supervision vs. Transfer Learning: Robust Biomedical Image Analysis Against Adversarial Attacks. ISBI 2020: 1159-1163 - [c25]Deepak Anand, Shrey Gadiya, Amit Sethi:
Histographs: graphs in histopathology. Medical Imaging: Digital Pathology 2020: 113200O - [i16]Abhijeet Patil, Dipesh Tamboli, Swati Meena, Deepak Anand, Amit Sethi:
Breast Cancer Histopathology Image Classification and Localization using Multiple Instance Learning. CoRR abs/2003.00823 (2020) - [i15]Hrushikesh Loya, Pranav Poduval, Deepak Anand, Neeraj Kumar, Amit Sethi:
Uncertainty Estimation in Cancer Survival Prediction. CoRR abs/2003.08573 (2020) - [i14]Mukesh Kumar Vishal, Dipesh Tamboli, Abhijeet Patil, Rohit Saluja, Biplab Banerjee, Amit Sethi, Raju Dhandapani, Sudhir Kumar, Rabi Narayan Sahoo, Viswanathan Chinnusamy, J. Adinarayana:
Image-based phenotyping of diverse Rice (Oryza Sativa L.) Genotypes. CoRR abs/2004.02498 (2020) - [i13]Pranav Poduval, Hrushikesh Loya, Amit Sethi:
Functional Space Variational Inference for Uncertainty Estimation in Computer Aided Diagnosis. CoRR abs/2005.11797 (2020) - [i12]Mookund Sureka, Abhijeet Patil, Deepak Anand, Amit Sethi:
Visualization for Histopathology Images using Graph Convolutional Neural Networks. CoRR abs/2006.09464 (2020) - [i11]Deepak Anand, Gaurav Patel, Yaman Dang, Amit Sethi:
Switching Loss for Generalized Nucleus Detection in Histopathology. CoRR abs/2008.03750 (2020) - [i10]Himanshu Pradeep Aswani, Amit Sethi:
Activation Functions: Do They Represent A Trade-Off Between Modular Nature of Neural Networks And Task Performance. CoRR abs/2009.07793 (2020) - [i9]Shubhang Bhatnagar, Darshan Tank, Sachin Goyal, Amit Sethi:
PAL : Pretext-based Active Learning. CoRR abs/2010.15947 (2020) - [i8]Abhijeet Patil, Mohd. Talha, Aniket Bhatia, Nikhil Cherian Kurian, Sammed Mangale, Sunil Patel, Amit Sethi:
Fast, Self Supervised, Fully Convolutional Color Normalization of H&E Stained Images. CoRR abs/2011.15000 (2020)
2010 – 2019
- 2019
- [j12]Safaa Eldeeb, Murat Akçakaya, Matthew Sybeldon, Stephen T. Foldes, Emiliano Santarnecchi, Alvaro Pascual-Leone, Amit Sethi:
EEG-based functional connectivity to analyze motor recovery after stroke: A pilot study. Biomed. Signal Process. Control. 49: 419-426 (2019) - [j11]Neeraj Kumar, Phani Krishna Uppala, Karthik Duddu, Hari Sreedhar, Vishal K. Varma, Grace Guzman, Michael J. Walsh, Amit Sethi:
Hyperspectral Tissue Image Segmentation Using Semi-Supervised NMF and Hierarchical Clustering. IEEE Trans. Medical Imaging 38(5): 1304-1313 (2019) - [j10]Kumar Yashashwi, Amit Sethi, Prasanna Chaporkar:
A Learnable Distortion Correction Module for Modulation Recognition. IEEE Wirel. Commun. Lett. 8(1): 77-80 (2019) - [c24]Deepak Anand, Goutham Ramakrishnan, Amit Sethi:
Fast GPU-Enabled Color Normalization for Digital Pathology. IWSSIP 2019: 219-224 - [c23]Yaman Dang, Deepak Anand, Amit Sethi:
Pixel-wise Segmentation of Right Ventricle of Heart. TENCON 2019: 1797-1802 - [c22]Viraf Patrawala, Nikhil Cherian Kurian, Amit Sethi:
Improving Histopathology Classification using Learnable Preprocessing. TENCON 2019: 2460-2465 - [i7]Goutham Ramakrishnan, Deepak Anand, Amit Sethi:
Fast GPU-Enabled Color Normalization for Digital Pathology. CoRR abs/1901.03088 (2019) - [i6]Shrey Gadiya, Deepak Anand, Amit Sethi:
Histographs: Graphs in Histopathology. CoRR abs/1908.05020 (2019) - [i5]Yaman Dang, Deepak Anand, Amit Sethi:
Pixel-wise Segmentation of Right Ventricle of Heart. CoRR abs/1908.08004 (2019) - 2018
- [j9]Neeraj Kumar, Amit Sethi:
Super Resolution by Comprehensively Exploiting Dependencies of Wavelet Coefficients. IEEE Trans. Multim. 20(2): 298-309 (2018) - [c21]Aditya Golatkar, Deepak Anand, Amit Sethi:
Classification of Breast Cancer Histology Using Deep Learning. ICIAR 2018: 837-844 - [i4]Aditya Golatkar, Deepak Anand, Amit Sethi:
Classification of Breast Cancer Histology using Deep Learning. CoRR abs/1802.08080 (2018) - [i3]Shrey Gadiya, Deepak Anand, Amit Sethi:
Some New Layer Architectures for Graph CNN. CoRR abs/1811.00052 (2018) - 2017
- [j8]Neeraj Kumar, Ruchika Verma, Amit Sethi:
Convolutional neural networks for wavelet domain super resolution. Pattern Recognit. Lett. 90: 65-71 (2017) - [j7]Neeraj Kumar, Ruchika Verma, Sanuj Sharma, Surabhi Bhargava, Abhishek Vahadane, Amit Sethi:
A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology. IEEE Trans. Medical Imaging 36(7): 1550-1560 (2017) - [c20]Kothapalli Vignesh, Gaurav Kumar Yadav, Amit Sethi:
Abnormal Event Detection on BMTT-PETS 2017 Surveillance Challenge. CVPR Workshops 2017: 2161-2168 - [c19]Gaurav Kumar Yadav, Amit Sethi:
Action recognition using spatio-temporal differential motion. ICIP 2017: 3415-3419 - [c18]Neeraj Kumar, Ruchika Verma, Ashish Arora, Abhay Kumar, Sanchit Gupta, Amit Sethi, Peter H. Gann:
Convolutional neural networks for prostate cancer recurrence prediction. Medical Imaging: Digital Pathology 2017: 101400H - [c17]Lingdao Sha, Dan Schonfeld, Amit Sethi:
Color normalization of histology slides using graph regularized sparse NMF. Medical Imaging: Digital Pathology 2017: 1014010 - 2016
- [j6]Abhishek Vahadane, Tingying Peng, Amit Sethi, Shadi Albarqouni, Lichao Wang, Maximilian Baust, Katja Steiger, Anna Melissa Schlitter, Irene Esposito, Nassir Navab:
Structure-Preserving Color Normalization and Sparse Stain Separation for Histological Images. IEEE Trans. Medical Imaging 35(8): 1962-1971 (2016) - [j5]Neeraj Kumar, Amit Sethi:
Fast Learning-Based Single Image Super-Resolution. IEEE Trans. Multim. 18(8): 1504-1515 (2016) - [c16]Gaurav Kumar Yadav, Prakhar Shukla, Amit Sethi:
Action recognition using interest points capturing differential motion information. ICASSP 2016: 1881-1885 - [c15]Ruchika Verma, Neeraj Kumar, Amit Sethi, Peter H. Gann:
Detecting multiple sub-types of breast cancer in a single patient. ICIP 2016: 2648-2652 - [c14]Abhishek Vahadane, Neeraj Kumar, Amit Sethi:
Learning based super-resolution of histological images. ISBI 2016: 816-819 - 2015
- [c13]Neeraj Kumar, Amit Sethi:
On spatial neighborhood of patch-based super resolution. ICIP 2015: 497-501 - [c12]Abhishek Vahadane, Tingying Peng, Shadi Albarqouni, Maximilian Baust, Katja Steiger, Anna Melissa Schlitter, Amit Sethi, Irene Esposito, Nassir Navab:
Structure-preserved color normalization for histological images. ISBI 2015: 1012-1015 - [i2]Neeraj Kumar, Ranti Dev Sharma, Animesh Karmakar, Amit Sethi:
Deep Learning-Based Image Kernel for Inductive Transfer. CoRR abs/1512.04086 (2015) - 2014
- [c11]Gaurav Kumar Yadav, Amit Sethi:
A Flow-based Interest Point Detector for Action Recognition in Videos. ICVGIP 2014: 41:1-41:7 - [c10]Rahul Nallamothu, T. Vineeth, Gaurav Kumar Yadav, Amit Sethi, Tony Jacob:
Interest Point Detection in Videos Using Long Point Trajectories. ICVGIP 2014: 70:1-70:5 - 2013
- [j4]Sean Debroni, Erin Delisle, Wendy J. Myrvold, Amit Sethi, Joseph Whitney, Jennifer Woodcock, Patrick W. Fowler, Benoit de La Vaissière, Michel Deza:
Maximum independent sets of the 120-cell and other regular polytopes. Ars Math. Contemp. 6(2): 197-210 (2013) - [c9]Devendra Singh Sachan, Umesh Tekwani, Amit Sethi:
Sports Video Classification from Multimodal Information Using Deep Neural Networks. AAAI Fall Symposia 2013 - [c8]Abhishek Vahadane, Amit Sethi:
Towards generalized nuclear segmentation in histological images. BIBE 2013: 1-4 - [c7]Tushar Sandhan, Amit Sethi, Tushar Srivastava, Jin Young Choi:
Unsupervised learning approach for abnormal event detection in surveillance video by revealing infrequent patterns. IVCNZ 2013: 494-499 - 2012
- [c6]Naveen Kumar Rai, Shikha Chourasia, Amit Sethi:
An Efficient Neural Network Based Background Subtraction Method. BIC-TA (1) 2012: 453-460 - [c5]Neeraj Kumar, Naveen Kumar Rai, Amit Sethi:
Learning to predict super resolution wavelet coefficients. ICPR 2012: 3468-3471
2000 – 2009
- 2007
- [j3]Amit Sethi, Mandar Rahurkar, Thomas S. Huang:
Event Detection Using "Variable Module Graphs" for Home Care Applications. EURASIP J. Adv. Signal Process. 2007 (2007) - 2006
- [b1]Amit Sethi:
Interaction Between Modules in Learning Systems for Vision Applications. University of Illinois Urbana-Champaign, USA, 2006 - [j2]Yasutaka Furukawa, Amit Sethi, Jean Ponce, David J. Kriegman:
Robust Structure and Motion from Outlines of Smooth Curved Surfaces. IEEE Trans. Pattern Anal. Mach. Intell. 28(2): 302-315 (2006) - 2005
- [c4]Amit Sethi, Mandar Rahurkar, Thomas S. Huang:
Variable module graphs: a framework for inference and learning in modular vision systems. ICIP (2) 2005: 1326-1329 - 2004
- [j1]Amit Sethi, David Renaudie, David J. Kriegman, Jean Ponce:
Curve and Surface Duals and the Recognition of Curved 3D Objects from their Silhouettes. Int. J. Comput. Vis. 58(1): 73-86 (2004) - [c3]Yasutaka Furukawa, Amit Sethi, Jean Ponce, David J. Kriegman:
Structure and Motion from Images of Smooth Textureless Objects. ECCV (2) 2004: 287-298 - [c2]Mei Han, Amit Sethi, Wei Hua, Yihong Gong:
A detection-based multiple object tracking method. ICIP 2004: 3065-3068 - [i1]Matthew J. Campagna, Amit Sethi:
Key Recovery Method for CRT Implementation of RSA. IACR Cryptol. ePrint Arch. 2004: 147 (2004) - 2002
- [c1]Svetlana Lazebnik, Amit Sethi, Cordelia Schmid, David J. Kriegman, Jean Ponce, Martial Hebert:
On Pencils of Tangent Planes and the Recognition of Smooth 3D Shapes from Silhouettes. ECCV (3) 2002: 651-665
Coauthor Index
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