Saeid Asgari Taghanaki | DeepAI

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∙ 09/06/2023

SLiMe: Segment Like Me

Significant strides have been made using large vision-language models, l...

0 Aliasghar Khani, et al. ∙

∙ 09/01/2023

Learned Visual Features to Textual Explanations

Interpreting the learned features of vision models has posed a longstand...

0 Saeid Asgari Taghanaki, et al. ∙

∙ 07/08/2023

Sketch-A-Shape: Zero-Shot Sketch-to-3D Shape Generation

Significant progress has recently been made in creative applications of ...

0 Aditya Sanghi, et al. ∙

∙ 09/30/2022

MaskTune: Mitigating Spurious Correlations by Forcing to Explore

A fundamental challenge of over-parameterized deep learning models is le...

6 Saeid Asgari Taghanaki, et al. ∙

∙ 07/04/2022

Counterbalancing Teacher: Regularizing Batch Normalized Models for Robustness

Batch normalization (BN) is a ubiquitous technique for training deep neu...

4 Saeid Asgari Taghanaki, et al. ∙

∙ 06/11/2021

Robust Representation Learning via Perceptual Similarity Metrics

A fundamental challenge in artificial intelligence is learning useful re...

0 Saeid Asgari Taghanaki, et al. ∙

∙ 11/23/2020

RobustPointSet: A Dataset for Benchmarking Robustness of Point Cloud Classifiers

The 3D deep learning community has seen significant strides in pointclou...

0 Saeid Asgari Taghanaki, et al. ∙

∙ 07/09/2020

PointMask: Towards Interpretable and Bias-Resilient Point Cloud Processing

Deep classifiers tend to associate a few discriminative input variables ...

0 Saeid Asgari Taghanaki, et al. ∙

∙ 05/12/2020

Jigsaw-VAE: Towards Balancing Features in Variational Autoencoders

The latent variables learned by VAEs have seen considerable interest as ...

5 Saeid Asgari Taghanaki, et al. ∙

∙ 11/16/2019

Signed Input Regularization

Over-parameterized deep models usually over-fit to a given training dist...

16 Saeid Asgari Taghanaki, et al. ∙

∙ 03/28/2019

InfoMask: Masked Variational Latent Representation to Localize Chest Disease

The scarcity of richly annotated medical images is limiting supervised d...

24 Saeid Asgari Taghanaki, et al. ∙

∙ 03/03/2019

A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations

The linear and non-flexible nature of deep convolutional models makes th...

0 Saeid Asgari Taghanaki, et al. ∙

∙ 07/09/2018

Vulnerability Analysis of Chest X-Ray Image Classification Against Adversarial Attacks

Recently, there have been several successful deep learning approaches fo...

0 Saeid Asgari Taghanaki, et al. ∙

∙ 05/08/2018

Combo Loss: Handling Input and Output Imbalance in Multi-Organ Segmentation

Simultaneous segmentation of multiple organs from different medical imag...

2 Saeid Asgari Taghanaki, et al. ∙

∙ 04/14/2018

Select, Attend, and Transfer: Light, Learnable Skip Connections

Skip connections in deep networks have improved both segmentation and cl...

0 Saeid Asgari Taghanaki, et al. ∙

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