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ORCIDNilesh A. Ahuja
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Journal Articles
- 2022
[j4]Meena Arunachalam, Vrushabh Sanghavi, Samudyatha Kaira, Nilesh A. Ahuja:
End-to-End Industrial IoT: Software Optimization and Acceleration. IEEE Internet Things Mag. 5(1): 48-53 (2022)- 2007
- [j3]Nilesh A. Ahuja, Nirmal K. Bose:
Design of Large Field-of-View High-Resolution Miniaturized Imaging System. EURASIP J. Adv. Signal Process. 2007 (2007) - 2006
- [j2]Nirmal K. Bose, Nilesh A. Ahuja:
Superresolution and noise filtering using moving least squares. IEEE Trans. Image Process. 15(8): 2239-2248 (2006) - 2005
- [j1]Nilesh A. Ahuja, Nirmal K. Bose:
Spatiotemporal-bandwidth product of m-dimensional signals. IEEE Signal Process. Lett. 12(2): 123-125 (2005)
Conference and Workshop Papers
- 2024
- [c12]Vinay Kashyap, Nilesh A. Ahuja, Omesh Tickoo:
Compression without Compromise: Optimizing Point Cloud Object Detection with Bottleneck Architectures For Split Computing. ICME Workshops 2024: 1-6 - 2023
- [c11]Ibrahima J. Ndiour, Nilesh A. Ahuja, Ergin Utku Genc, Omesh Tickoo:
FRE: A Fast Method For Anomaly Detection And Segmentation. BMVC 2023: 614-616 - [c10]Nilesh A. Ahuja, Parual Datta, Bhavya Kanzariya, V. Srinivasa Somayazulu, Omesh Tickoo:
Neural Rate Estimator and Unsupervised Learning for Efficient Distributed Image Analytics in Split-DNN models. CVPR 2023: 2022-2030 - 2022
- [c9]Amrutha Machireddy, Ranganath Krishnan, Nilesh A. Ahuja, Omesh Tickoo:
Continual Active Adaptation to Evolving Distributional Shifts. CVPR Workshops 2022: 3443-3449 - [c8]Amanda Rios, Nilesh A. Ahuja, Ibrahima J. Ndiour, Ergin Utku Genc, Laurent Itti, Omesh Tickoo:
incDFM: Incremental Deep Feature Modeling for Continual Novelty Detection. ECCV (25) 2022: 588-604 - [c7]Samet Akcay, Dick Ameln
, Ashwin Vaidya, Barath Lakshmanan, Nilesh A. Ahuja, Ergin Utku Genc:
Anomalib: A Deep Learning Library for Anomaly Detection. ICIP 2022: 1706-1710 - [c6]Ibrahima J. Ndiour, Nilesh A. Ahuja, Omesh Tickoo:
Subspace Modeling for Fast Out-Of-Distribution and Anomaly Detection. ICIP 2022: 3041-3045 - [c5]Parual Datta, Nilesh A. Ahuja, V. Srinivasa Somayazulu, Omesh Tickoo:
A Low-Complexity Approach to Rate-Distortion Optimized Variable Bit-Rate Compression for Split DNN Computing. ICPR 2022: 182-188 - 2021
- [c4]Chaunte Lacewell, Nilesh A. Ahuja, Pablo Munoz, Parual Datta, Ragaad AlTarawneh, Vui Seng Chua, Nilesh Jain, Omesh Tickoo, Ravi Iyer:
E2E Visual Analytics: Achieving >10X Edge/Cloud Optimizations. NAS 2021: 1-8 - 2020
- [c3]Neel Patwa, Nilesh A. Ahuja, V. Srinivasa Somayazulu, Omesh Tickoo, Srenivas Varadarajan, Shashidhar G. Koolagudi:
Semantic-Preserving Image Compression. ICIP 2020: 1281-1285 - 2017
- [c2]Nilesh A. Ahuja, Mahesh Subedar, Omesh Tickoo, Yeongseon Lee:
A Factorization Approach for Enabling Structure-from-Motion/SLAM Using Integer Arithmetic. ICCV Workshops 2017: 554-562 - 2006
- [c1]Nilesh A. Ahuja, Nirmal K. Bose:
Multidimensional Generalized Sampling Theorem for wavelet Based Image Superresolution. ICIP 2006: 1589-1592
Informal and Other Publications
- 2023
- [i13]Alon Harell, Yalda Foroutan, Nilesh A. Ahuja, Parual Datta, Bhavya Kanzariya, V. Srinivasa Somayazulu, Omesh Tickoo, Anderson de Andrade, Ivan V. Bajic:
Rate-Distortion Theory in Coding for Machines and its Application. CoRR abs/2305.17295 (2023) - 2022
- [i12]Samet Akcay, Dick Ameln, Ashwin Vaidya, Barath Lakshmanan, Nilesh A. Ahuja, Ergin Utku Genc:
Anomalib: A Deep Learning Library for Anomaly Detection. CoRR abs/2202.08341 (2022) - [i11]Ibrahima J. Ndiour, Nilesh A. Ahuja, Omesh Tickoo:
Subspace Modeling for Fast Out-Of-Distribution and Anomaly Detection. CoRR abs/2203.10422 (2022) - [i10]Parual Datta, Nilesh A. Ahuja, V. Srinivasa Somayazulu, Omesh Tickoo:
A Low-Complexity Approach to Rate-Distortion Optimized Variable Bit-Rate Compression for Split DNN Computing. CoRR abs/2208.11596 (2022) - [i9]Ibrahima J. Ndiour, Nilesh A. Ahuja, Ergin Utku Genc, Omesh Tickoo:
FRE: A Fast Method For Anomaly Detection And Segmentation. CoRR abs/2211.12650 (2022) - 2021
- [i8]Ergin Utku Genc, Nilesh A. Ahuja, Ibrahima J. Ndiour, Omesh Tickoo:
Energy-Based Anomaly Detection and Localization. CoRR abs/2105.03270 (2021) - [i7]Ranganath Krishnan, Alok Sinha, Nilesh A. Ahuja, Mahesh Subedar, Omesh Tickoo, Ravi Iyer:
Mitigating Sampling Bias and Improving Robustness in Active Learning. CoRR abs/2109.06321 (2021) - [i6]Ranganath Krishnan, Nilesh A. Ahuja, Alok Sinha, Mahesh Subedar, Omesh Tickoo, Ravi Iyer:
Improving Robustness and Efficiency in Active Learning with Contrastive Loss. CoRR abs/2109.06873 (2021) - 2020
- [i5]Ibrahima J. Ndiour, Nilesh A. Ahuja, Omesh Tickoo:
Out-Of-Distribution Detection With Subspace Techniques And Probabilistic Modeling Of Features. CoRR abs/2012.04250 (2020) - 2019
- [i4]Javier Felip, Nilesh A. Ahuja, David Gómez-Gutiérrez, Omesh Tickoo, Vikash Mansinghka:
Real-time Approximate Bayesian Computation for Scene Understanding. CoRR abs/1905.13307 (2019) - [i3]Nilesh A. Ahuja, Ibrahima J. Ndiour, Trushant Kalyanpur, Omesh Tickoo:
Probabilistic Modeling of Deep Features for Out-of-Distribution and Adversarial Detection. CoRR abs/1909.11786 (2019) - [i2]Mahesh Subedar, Nilesh A. Ahuja, Ranganath Krishnan, Ibrahima J. Ndiour, Omesh Tickoo:
Deep Probabilistic Models to Detect Data Poisoning Attacks. CoRR abs/1912.01206 (2019) - [i1]Javier Felip, Nilesh A. Ahuja, Omesh Tickoo:
Tree pyramidal adaptive importance sampling. CoRR abs/1912.08434 (2019)
Coauthor Index
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