Adde, L.[Lars]
* 2014: Motion Segmentation with Weak Labeling Priors
* 2015: Weakly supervised motion segmentation with particle matching
Addepalli, S.
* 2020: Saliency-Driven Class Impressions For Feature Visualization Of Deep Neural Networks
* 2020: Towards Achieving Adversarial Robustness by Enforcing Feature Consistency Across Bit Planes
* 2021: Boosting Adversarial Robustness using Feature Level Stochastic Smoothing
* 2022: Scaling Adversarial Training to Large Perturbation Bounds
* 2022: Towards Data-Free Model Stealing in a Hard Label Setting
* 2022: Towards Efficient and Effective Self-supervised Learning of Visual Representations
* 2023: Certified Adversarial Robustness Within Multiple Perturbation Bounds
* 2023: DART: Diversify-Aggregate-Repeat Training Improves Generalization of Neural Networks
* 2023: RMLVQA: A Margin Loss Approach For Visual Question Answering with Language Biases
Includes: Addepalli, S. Addepalli, S.[Sravanti]
9 for Addepalli, S.
Addesso, L.[Luca]
* 2017: Organizing egocentric videos of daily living activities
Addesso, P.
* 2014: Class of Cloud Detection Algorithms Based on a MAP-MRF Approach in Space and Time, A
* 2017: Hyperspectral image inpainting based on collaborative total variation
* 2019: Pansharpening Based on Deconvolution for Multiband Filter Estimation
* 2020: Data-Driven Model-Based Regression Applied to Panchromatic Sharpening, A
* 2020: Editorial for Special Issue Remote Sensing for Target Object Detection and Identification
* 2021: Hyperspectral Sharpening Approaches Using Satellite Multiplatform Data
* 2021: Improved Version of the Generalized Laplacian Pyramid Algorithm for Pansharpening, An
Includes: Addesso, P. Addesso, P.[Paolo]
7 for Addesso, P.