Search Results for author: Dan Schonfeld

Found 7 papers, 0 papers with code

Exploit Visual Dependency Relations for Semantic Segmentation

no code implementations CVPR 2021 Mingyuan Liu, Dan Schonfeld, Wei Tang

Inter-class reasoning then performs spatial and semantic reasoning based on the dependency relations among different object categories.

Semantic Segmentation

Deep-URL: A Model-Aware Approach To Blind Deconvolution Based On Deep Unfolded Richardson-Lucy Network

no code implementations3 Feb 2020 Chirag Agarwal, Shahin Khobahi, Arindam Bose, Mojtaba Soltanalian, Dan Schonfeld

The lack of interpretability in current deep learning models causes serious concerns as they are extensively used for various life-critical applications.

Removing input features via a generative model to explain their attributions to classifier's decisions

no code implementations25 Sep 2019 Chirag Agarwal, Dan Schonfeld, Anh Nguyen

Interpretability methods often measure the contribution of an input feature to an image classifier's decisions by heuristically removing it via e. g. blurring, adding noise, or graying out, which often produce unrealistic, out-of-samples.

Improving Adversarial Robustness by Encouraging Discriminative Features

no code implementations1 Nov 2018 Chirag Agarwal, Anh Nguyen, Dan Schonfeld

Intuitively, the center loss encourages DNNs to simultaneously learns a center for the deep features of each class, and minimize the distances between the intra-class deep features and their corresponding class centers.

Adversarial Robustness

An Explainable Adversarial Robustness Metric for Deep Learning Neural Networks

no code implementations5 Jun 2018 Chirag Agarwal, Bo Dong, Dan Schonfeld, Anthony Hoogs

Instead of simply measuring a DNN's adversarial robustness in the input domain, as previous works, the proposed NSS is built on top of insightful mathematical understanding of the adversarial attack and gives a more explicit explanation of the robustness.

Adversarial Attack Adversarial Robustness +3

Convergence of backpropagation with momentum for network architectures with skip connections

no code implementations21 May 2017 Chirag Agarwal, Joe Klobusicky, Dan Schonfeld

We study a class of deep neural networks with networks that form a directed acyclic graph (DAG).

Compressive Sensing of Sparse Tensors

no code implementations24 May 2013 Shmuel Friedland, Qun Li, Dan Schonfeld

We then compare the performance of the proposed method with Kronecker compressive sensing (KCS) and multi way compressive sensing (MWCS).

Compressive Sensing Data Compression

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