| Graph Matching and Pseudo-Label Guided Deep Unsupervised Domain Adaptation D Das, CSG Lee International Conference on Artificial Neural Networks (ICANN) 2018, 2018 | 176* | 2018 |
| A Two-Stage Approach to Few-Shot Learning for Image Recognition D Das, CSG Lee IEEE Transactions on Image Processing (TIP), 2019 | 152 | 2019 |
| Economic impact of COVID-19 pandemic S Roy, D Das Technical Report, 1-29, 2020 | 130 | 2020 |
| Sample-to-Sample Correspondence for Unsupervised Domain Adaptation D Das, CSG Lee Engineering Applications of Artificial Intelligence (EAAI) (73) 80-91, 2018 | 73 | 2018 |
| Unsupervised Domain Adaptation using Regularized Hyper-graph matching D Das, CSG Lee IEEE International Conference on Image Processing (ICIP) 2018, 2018 | 71 | 2018 |
| A power-line interference canceler based on sliding DFT phase locking scheme for ECG signals S Mishra, D Das, R Kumar, P Sumathi IEEE transactions on Instrumentation and measurement 64 (1), 132-142, 2014 | 66 | 2014 |
| ConFeSS: A Framework for Single Source Cross-Domain Few-Shot Learning D Das, S Yun, F Porikli International Conference on Learning Representations (ICLR), 2022 | 54 | 2022 |
| Zero-shot Image Recognition Using Relational Matching, Adaptation and Calibration D Das, CSG Lee International Joint Conference on Neural Networks (IJCNN), 2019 | 40 | 2019 |
| Progressive Random Convolutions for Single Domain Generalization S Choi, D Das, S Choi, S Yang, H Park, S Yun IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 | 32 | 2023 |
| Multi-step Online Unsupervised Domain Adaptation JH Moon, D Das, CSG Lee IEEE International Conference on Acoustics, Speech, and Signal Processing …, 2020 | 25* | 2020 |
| Towards Open-Set Test-Time Adaptation Utilizing the Wisdom of Crowds in Entropy Minimization J Lee, D Das, J Choo, S Choi IEEE/CVF International Conference on Computer Vision (ICCV), 2023 | 17 | 2023 |
| Panoptic, Instance and Semantic Relations: A Relational Context Encoder to Enhance Panoptic Segmentation S Borse, H Park, H Cai, D Das, R Garrepalli, F Porikli IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 | 17* | 2022 |
| Cross-Scene Trajectory Level Intention Inference using Gaussian Process Regression and Naive Registration D Das, CSG Lee Technical Report, 2018 | 14 | 2018 |
| Few-shot Image Recognition with Manifolds D Das, JH Moon, CSG Lee International Symposium on Visual Computing (ISVC), 2020 | 13 | 2020 |
| DejaVu: Conditional Regenerative Learning to Enhance Dense Prediction S Borse, D Das, H Park, H Cai, R Garrepalli, F Porikli IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 | 10 | 2023 |
| A Multi-stage Framework with Mean Subspace Computation and Recursive Feedback for Online Unsupervised Domain Adaptation JH Moon, D Das, CSG Lee IEEE Transactions on Image Processing (TIP), 2022 | 10 | 2022 |
| Domain Agnostic Few-shot Learning for Speaker Verification S Yang, D Das, J Cho, H Park, S Yun ISCA Conference of the International Speech Communication Association …, 2022 | 9 | 2022 |
| Algorithm for a PSO tuned fuzzy controller of a DC motor D Das, A Ghosh International Journal of Computer Applications (IJCA) 73 (4), 2013 | 9 | 2013 |
| A Personalized Benchmark for Face Anti-spoofing D Belli, D Das, B Major, F Porikli IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Workshops, 2022 | 6 | 2022 |
| Distribution estimation to automate transformation policies for self-supervision S Yang, D Das, S Chang, S Yun, F Porikli arXiv preprint arXiv:2111.12265, 2021 | 6* | 2021 |
Fatih PorikliQualcomm, Australian National Universityanu.edu.au의 이메일 확인됨