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ORCIDSathyanarayanan N. Aakur
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2020 – today
- 2024
[j5]V. S. S. Bala Tripura Sathvika
, Nagilla Anmisha, Vada Thanmayi, M. Suchetha, Edwin Dhas D, S. Sehastrajit, Sathyanarayanan N. Aakur:
Pipelined Structure in the Classification of Skin Lesions Based on Alexnet CNN and SVM Model With Bi-Sectional Texture Features. IEEE Access 12: 57366-57380 (2024)- [j4]Snehith Sankineni, Aanchal Saraswat, M. Suchetha, Sathyanarayanan N. Aakur, S. Sehastrajit, Edwin Dhas D:
An insight on recent advancements and future perspectives in detection techniques of Parkinson's disease. Evol. Intell. 17(3): 1715-1731 (2024) - [j3]Sathyanarayanan N. Aakur, Vishalini R. Laguduva, Priyadharsini Ramamurthy, Akhilesh Ramachandran:
TEPI: Taxonomy-Aware Embedding and Pseudo-Imaging for Scarcely-Labeled Zero-Shot Genome Classification. IEEE J. Biomed. Health Informatics 28(4): 2385-2396 (2024) - [c27]Sanjoy Kundu, Shubham Trehan, Sathyanarayanan N. Aakur:
Discovering Novel Actions from Open World Egocentric Videos with Object-Grounded Visual Commonsense Reasoning. ECCV (59) 2024: 39-56 - [c26]Shenyuan Liang, Anuj Srivastava, Maurício Pamplona Segundo, Sudeep Sarkar, Sathyanarayanan N. Aakur:
Shape-Graph Matching Network (SGM-net): Registration for Statistical Shape Analysis. ISBI 2024: 1-4 - [i22]Sathyanarayanan N. Aakur, Vishalini R. Laguduva, Priyadharsini Ramamurthy, Akhilesh Ramachandran:
TEPI: Taxonomy-aware Embedding and Pseudo-Imaging for Scarcely-labeled Zero-shot Genome Classification. CoRR abs/2401.13219 (2024) - [i21]Sanjoy Kundu, Shubham Trehan, Sathyanarayanan N. Aakur:
ALGO: Object-Grounded Visual Commonsense Reasoning for Open-World Egocentric Action Recognition. CoRR abs/2406.05722 (2024) - [i20]Venkata Ragavendra Vavilthota, Ranjith Ramanathan, Sathyanarayanan N. Aakur:
Capturing Temporal Components for Time Series Classification. CoRR abs/2406.14456 (2024) - [i19]Shubham Trehan, Sathyanarayanan N. Aakur:
Self-supervised Multi-actor Social Activity Understanding in Streaming Videos. CoRR abs/2406.14472 (2024) - 2023
- [j2]Sathyanarayanan N. Aakur, Sudeep Sarkar:
Leveraging Symbolic Knowledge Bases for Commonsense Natural Language Inference Using Pattern Theory. IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 13185-13202 (2023) - [c25]Sanjoy Kundu, Sathyanarayanan N. Aakur:
IS-GGT: Iterative Scene Graph Generation with Generative Transformers. CVPR 2023: 6292-6301 - [c24]Shubham Trehan, Udhav Ramachandran, Ruth Scimeca, Sathyanarayanan N. Aakur:
ProtoKD: Learning from Extremely Scarce Data for Parasite Ova Recognition. ICMLA 2023: 683-688 - [i18]Sathyanarayanan N. Aakur, Sanjoy Kundu, Shubham Trehan:
Discovering Novel Actions in an Open World with Object-Grounded Visual Commonsense Reasoning. CoRR abs/2305.16602 (2023) - [i17]Shenyuan Liang, Maurício Pamplona Segundo, Sathyanarayanan N. Aakur, Sudeep Sarkar, Anuj Srivastava:
Shape-Graph Matching Network (SGM-net): Registration for Statistical Shape Analysis. CoRR abs/2308.06869 (2023) - [i16]Shubham Trehan, Udhav Ramachandran, Ruth Scimeca, Sathyanarayanan N. Aakur:
ProtoKD: Learning from Extremely Scarce Data for Parasite Ova Recognition. CoRR abs/2309.10210 (2023) - 2022
- [j1]Sathyanarayanan N. Aakur, Sanjoy Kundu, Nikhil Gunti:
Knowledge guided learning: Open world egocentric action recognition with zero supervision. Pattern Recognit. Lett. 156: 38-45 (2022) - [c23]Shengfang Ma, Yuting Zhou, K. Colton Flynn, Sathyanarayanan N. Aakur:
Peanut Seed Germination Detection from Aerial Images. AIPR 2022: 1-6 - [c22]Sathyanarayanan N. Aakur, Sudeep Sarkar:
Actor-Centered Representations for Action Localization in Streaming Videos. ECCV (38) 2022: 70-87 - [c21]Aditi Basu Bal, Ramy Mounir, Sathyanarayanan N. Aakur, Sudeep Sarkar, Anuj Srivastava:
Bayesian Tracking of Video Graphs Using Joint Kalman Smoothing and Registration. ECCV (35) 2022: 440-456 - [c20]Priyadharsini Ramamurthy, Sathyanarayanan N. Aakur:
ISD-QA: Iterative Distillation of Commonsense Knowledge from General Language Models for Unsupervised Question Answering. ICPR 2022: 1229-1235 - [c19]Shubham Trehan, Sathyanarayanan N. Aakur:
Towards Active Vision for Action Localization with Reactive Control and Predictive Learning. WACV 2022: 3391-3400 - [i15]Vishal Pallagani, Priyadharsini Ramamurthy, Vedant Khandelwal, Revathy Venkataramanan, Kausik Lakkaraju, Sathyanarayanan N. Aakur, Biplav Srivastava:
A Rich Recipe Representation as Plan to Support Expressive Multi Modal Queries on Recipe Content and Preparation Process. CoRR abs/2203.17109 (2022) - [i14]Sanjoy Kundu, Sathyanarayanan N. Aakur:
Iterative Scene Graph Generation with Generative Transformers. CoRR abs/2211.16636 (2022) - [i13]Sai Narayanan, Sathyanarayanan N. Aakur, Priyadharsini Ramamurthy, Arunkumar Bagavathi, Vishalini Ramnath, Akhilesh Ramachandran:
Scalable Pathogen Detection from Next Generation DNA Sequencing with Deep Learning. CoRR abs/2212.00015 (2022) - 2021
- [c18]Sathyanarayanan N. Aakur, Vineela Indla, Vennela Indla, Sai Narayanan, Arunkumar Bagavathi, Vishalini Laguduva Ramnath, Akhilesh Ramachandran:
Metagenome2Vec: Building Contextualized Representations for Scalable Metagenome Analysis. ICDM (Workshops) 2021: 500-507 - [c17]Thanh Thieu, Ha Do, Thanh Duong, Shi Pu, Sathyanarayanan N. Aakur, Saad Khan:
LexDivPara: A Measure of Paraphrase Quality with Integrated Sentential Lexical Complexity. IntelliSys (3) 2021: 1-10 - [c16]Sathyanarayanan N. Aakur, Sai Narayanan, Vineela Indla, Arunkumar Bagavathi, Vishalini Laguduva Ramnath, Akhilesh Ramachandran:
MG-NET: Leveraging Pseudo-imaging for Multi-modal Metagenome Analysis. MICCAI (5) 2021: 592-602 - [c15]Vineela Indla, Vennela Indla, Sai Narayanan, Akhilesh Ramachandran, Arunkumar Bagavathi, Vishalini Laguduva Ramnath, Sathyanarayanan N. Aakur:
Sim2Real for Metagenomes: Accelerating Animal Diagnostics with Adversarial Co-training. PAKDD (1) 2021: 164-175 - [c14]Sathyanarayanan N. Aakur, Arunkumar Bagavathi:
Unsupervised Gaze Prediction in Egocentric Videos by Energy-based Surprise Modeling. VISIGRAPP (5: VISAPP) 2021: 935-942 - [i12]Sathyanarayanan N. Aakur, Sudeep Sarkar:
Learning Actor-centered Representations for Action Localization in Streaming Videos using Predictive Learning. CoRR abs/2104.14131 (2021) - [i11]Sathyanarayanan N. Aakur, Sai Narayanan, Vineela Indla, Arunkumar Bagavathi, Vishalini Laguduva Ramnath, Akhilesh Ramachandran:
MG-NET: Leveraging Pseudo-Imaging for Multi-Modal Metagenome Analysis. CoRR abs/2107.09883 (2021) - [i10]Shubham Trehan, Sathyanarayanan N. Aakur:
Towards Active Vision for Action Localization with Reactive Control and Predictive Learning. CoRR abs/2111.05448 (2021) - [i9]Sathyanarayanan N. Aakur, Vineela Indla, Vennela Indla, Sai Narayanan, Arunkumar Bagavathi, Vishalini Laguduva Ramnath, Akhilesh Ramachandran:
Metagenome2Vec: Building Contextualized Representations for Scalable Metagenome Analysis. CoRR abs/2111.08001 (2021) - 2020
- [c13]Sanjoy Kundu, Nikhil Gunti, Bailey Hendrickson, Sunil More, Sathyanarayanan N. Aakur:
Benchmark and Evaluation of Low Resource Object Detection in Biomedical Images. AIPR 2020: 1-7 - [c12]Sathyanarayanan N. Aakur, Sudeep Sarkar:
Action Localization Through Continual Predictive Learning. ECCV (14) 2020: 300-317 - [c11]Sai Narayanan, Akhilesh Ramachandran, Sathyanarayanan N. Aakur, Arunkumar Bagavathi:
GRaDL: A Framework for Animal Genome Sequence Classification with Graph Representations and Deep Learning. ICMLA 2020: 1297-1303 - [c10]Vishalini R. Laguduva, Shakil Mahmud, Sathyanarayanan N. Aakur, Robert Karam, Srinivas Katkoori:
Dissecting Convolutional Neural Networks for Efficient Implementation on Constrained Platforms. VLSID 2020: 149-154 - [i8]Sathyanarayanan N. Aakur, Arunkumar Bagavathi:
Unsupervised Gaze Prediction in Egocentric Videos by Energy-based Surprise Modeling. CoRR abs/2001.11580 (2020) - [i7]Sathyanarayanan N. Aakur, Sudeep Sarkar:
Action Localization through Continual Predictive Learning. CoRR abs/2003.12185 (2020) - [i6]Sai Narayanan, Akhilesh Ramachandran, Sathyanarayanan N. Aakur, Arunkumar Bagavathi:
Genome Sequence Classification for Animal Diagnostics with Graph Representations and Deep Neural Networks. CoRR abs/2007.12791 (2020) - [i5]Sathyanarayanan N. Aakur, Sanjoy Kundu, Nikhil Gunti:
Knowledge Guided Learning: Towards Open Domain Egocentric Action Recognition with Zero Supervision. CoRR abs/2009.07470 (2020)
2010 – 2019
- 2019
- [b1]Sathyanarayanan N. Aakur:
Beyond Labels and Captions: Contextualizing Grounded Semantics for Explainable Visual Interpretation. University of South Florida, Tampa, USA, 2019 - [c9]Sathyanarayanan N. Aakur, Sudeep Sarkar:
A Perceptual Prediction Framework for Self Supervised Event Segmentation. CVPR 2019: 1197-1206 - [c8]Vishalini Laguduva Ramnath, Sathyanarayanan N. Aakur, Srinivas Katkoori:
Latent Space Modeling for Cloning Encrypted PUF-Based Authentication. IFIPIoT 2019: 142-158 - [c7]Vishalini R. Laguduva, Sheikh Ariful Islam, Sathyanarayanan N. Aakur, Srinivas Katkoori, Robert Karam:
Machine Learning Based IoT Edge Node Security Attack and Countermeasures. ISVLSI 2019: 670-675 - [c6]Sathyanarayanan N. Aakur, Daniel Sawyer, Sudeep Sarkar:
Fine-grained Action Detection in Untrimmed Surveillance Videos. WACV Workshops 2019: 38-40 - [c5]Sathyanarayanan N. Aakur, Fillipe D. M. de Souza, Sudeep Sarkar:
Going Deeper With Semantics: Video Activity Interpretation Using Semantic Contextualization. WACV 2019: 190-199 - [i4]Sathyanarayanan N. Aakur, Sudeep Sarkar:
Abductive Reasoning as Self-Supervision for Common Sense Question Answering. CoRR abs/1909.03099 (2019) - [i3]Vishalini R. Laguduva, Sheikh Ariful Islam, Sathyanarayanan N. Aakur, Srinivas Katkoori, Robert Karam:
Machine Learning based IoT Edge Node Security Attack and Countermeasures. CoRR abs/1909.07891 (2019) - 2018
- [c4]Sathyanarayanan N. Aakur, Fillipe D. M. de Souza, Sudeep Sarkar:
An Inherently Explainable Model for Video Activity Interpretation. AAAI Workshops 2018: 688-694 - [c3]Gilbert Rotich, Sathyanarayanan N. Aakur, Rodrigo Minetto, Maurício Pamplona Segundo, Sudeep Sarkar:
Using Semantic Relationships among Objects for Geospatial Land Use Classification. AIPR 2018: 1-7 - [c2]Sathyanarayanan N. Aakur, Daniel Sawyer, Michal Balazia, Sudeep Sarkar:
Fine-grained Action Detection in Long Surveillance Videos. TRECVID 2018 - [i2]Sathyanarayanan N. Aakur, Sudeep Sarkar:
A Perceptual Prediction Framework for Self Supervised Event Segmentation. CoRR abs/1811.04869 (2018) - 2017
- [c1]Sathyanarayanan N. Aakur, Fillipe D. M. de Souza, Sudeep Sarkar:
Towards a Knowledge-Based Approach for Generating Video Descriptions. CRV 2017: 24-31 - [i1]Sathyanarayanan N. Aakur, Fillipe D. M. de Souza, Sudeep Sarkar:
Exploiting Semantic Contextualization for Interpretation of Human Activity in Videos. CoRR abs/1708.03725 (2017)
Coauthor Index
aka: Vishalini Laguduva Ramnath
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last updated on 2024-12-02 22:28 CET by the dblp team
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