Mohammad Sabokrou

research

∙ 07/04/2023

Mitigating Bias: Enhancing Image Classification by Improving Model Explanations

Deep learning models have demonstrated remarkable capabilities in learni...

0 Raha Ahmadi, et al. ∙

research

∙ 06/27/2023

IMPOSITION: Implicit Backdoor Attack through Scenario Injection

This paper presents a novel backdoor attack called IMPlicit BackdOor Att...

0 Mozhgan PourKeshavarz, et al. ∙

research

∙ 06/14/2023

Global-Local Processing in Convolutional Neural Networks

Convolutional Neural Networks (CNNs) have achieved outstanding performan...

2 Zahra Rezvani, et al. ∙

research

∙ 06/10/2023

Revealing Model Biases: Assessing Deep Neural Networks via Recovered Sample Analysis

This paper proposes a straightforward and cost-effective approach to ass...

2 Mohammad Mahdi Mehmanchi, et al. ∙

research

∙ 06/06/2023

Expanding Explainability Horizons: A Unified Concept-Based System for Local, Global, and Misclassification Explanations

Explainability of intelligent models has been garnering increasing atten...

5 Fatemeh Aghaeipoor, et al. ∙

research

∙ 05/30/2023

Quantifying Overfitting: Evaluating Neural Network Performance through Analysis of Null Space

Machine learning models that are overfitted/overtrained are more vulnera...

0 Hossein Rezaei, et al. ∙

research

∙ 11/20/2022

Are Out-of-Distribution Detection Methods Reliable?

This paper establishes a novel evaluation framework for assessing the pe...

7 Vahid Reza Khazaie, et al. ∙

research

∙ 07/22/2022

MobileDenseNet: A new approach to object detection on mobile devices

Object detection problem solving has developed greatly within the past f...

3 Mohammad Hajizadeh, et al. ∙

research

∙ 05/28/2022

Fake It Till You Make It: Near-Distribution Novelty Detection by Score-Based Generative Models

We aim for image-based novelty detection. Despite considerable progress,...

6 Hossein Mirzaei, et al. ∙

research

∙ 01/31/2022

Deep-Disaster: Unsupervised Disaster Detection and Localization Using Visual Data

Social media plays a significant role in sharing essential information, ...

6 Soroor Shekarizadeh, et al. ∙

research

∙ 01/05/2022

All You Need In Sign Language Production

Sign Language is the dominant form of communication language used in the...

3 Razieh Rastgoo, et al. ∙

research

∙ 10/26/2021

A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges

Machine learning models often encounter samples that are diverged from t...

17 Mohammadreza Salehi, et al. ∙

research

∙ 09/02/2021

Multi-Modal Zero-Shot Sign Language Recognition

Zero-Shot Learning (ZSL) has rapidly advanced in recent years. Towards o...

10 Razieh Rastgoo, et al. ∙

research

∙ 03/29/2021

Sign Language Production: A Review

Sign Language is the dominant yet non-primary form of communication lang...

6 Razieh Rastgoo, et al. ∙

research

∙ 03/29/2021

ClaRe: Practical Class Incremental Learning By Remembering Previous Class Representations

This paper presents a practical and simple yet efficient method to effec...

4 Bahram Mohammadi, et al. ∙

research

∙ 03/22/2021

ZS-IL: Looking Back on Learned ExperiencesFor Zero-Shot Incremental Learning

Classical deep neural networks are limited in their ability to learn fro...

7 Mozhgan PourKeshavarz, et al. ∙

research

∙ 03/18/2021

Ano-Graph: Learning Normal Scene Contextual Graphs to Detect Video Anomalies

Video anomaly detection has proved to be a challenging task owing to its...

10 Masoud Pourreza, et al. ∙

research

∙ 03/02/2021

Image/Video Deep Anomaly Detection: A Survey

The considerable significance of Anomaly Detection (AD) problem has rece...

14 Bahram Mohammadi, et al. ∙

research

∙ 06/29/2020

Cluster-Based Partitioning of Convolutional Neural Networks, A Solution for Computational Energy and Complexity Reduction

In this paper, we propose a novel solution to reduce the computational c...

14 Ali Mirzaeian, et al. ∙

research

∙ 06/26/2020

Learning Diverse Latent Representations for Improving the Resilience to Adversarial Attacks

This paper proposes an ensemble learning model that is resistant to adve...

0 Ali Mirzaeian, et al. ∙

research

∙ 06/20/2020

G2D: Generate to Detect Anomalies

In this paper, we propose a novel method for irregularity detection. Pre...

31 Masoud Pourreza, et al. ∙

research

∙ 06/20/2020

G2D: Generate to Detect Anomaly

In this paper, we propose a novel method for irregularity detection. Pre...

8 Masoud Pourreza, et al. ∙

research

∙ 02/12/2020

Deep-HR: Fast Heart Rate Estimation from Face Video Under Realistic Conditions

This paper presents a novel method for remote heart rate (HR) estimation...

22 Mohammad Sabokrou, et al. ∙

research

∙ 01/16/2020

Code-Bridged Classifier (CBC): A Low or Negative Overhead Defense for Making a CNN Classifier Robust Against Adversarial Attacks

In this paper, we propose Code-Bridged Classifier (CBC), a framework for...

12 Farnaz Behnia, et al. ∙

research

∙ 11/08/2019

AutoIDS: Auto-encoder Based Method for Intrusion Detection System

Intrusion Detection System (IDS) is one of the most effective solutions ...

0 Mohammed Gharib, et al. ∙

research

∙ 08/27/2019

Self-Supervised Representation Learning via Neighborhood-Relational Encoding

In this paper, we propose a novel self-supervised representation learnin...

18 Mohammad Sabokrou, et al. ∙

research

∙ 07/12/2019

AVD: Adversarial Video Distillation

In this paper, we present a simple yet efficient approach for video repr...

7 Mohammad Tavakolian, et al. ∙

research

∙ 04/25/2019

End-to-End Adversarial Learning for Intrusion Detection in Computer Networks

This paper presents a simple yet efficient method for an anomaly-based I...

0 Bahram Mohammadi, et al. ∙

research

∙ 06/24/2018

Online Signature Verification using Deep Representation: A new Descriptor

This paper presents an accurate method for verifying online signatures. ...

0 Mohammad Hajizadeh_Saffar, et al. ∙

research

∙ 06/16/2018

Semantic Video Segmentation: A Review on Recent Approaches

This paper gives an overview on semantic segmentation consists of an exp...

0 Mohammad Hajizadeh_Saffar, et al. ∙

research

∙ 05/24/2018

AVID: Adversarial Visual Irregularity Detection

Real-time detection of irregularities in visual data is very invaluable ...

2 Mohammad Sabokrou, et al. ∙

research

∙ 02/25/2018

Adversarially Learned One-Class Classifier for Novelty Detection

Novelty detection is the process of identifying the observation(s) that ...

0 Mohammad Sabokrou, et al. ∙

research

∙ 02/17/2018

Towards Principled Design of Deep Convolutional Networks: Introducing SimpNet

Major winning Convolutional Neural Networks (CNNs), such as VGGNet, ResN...

0 Seyyed Hossein Hasanpour, et al. ∙

research

∙ 09/03/2016

Deep-Anomaly: Fully Convolutional Neural Network for Fast Anomaly Detection in Crowded Scenes

The detection of abnormal behaviours in crowded scenes has to deal with ...

0 Mohammad Sabokrou, et al. ∙

research

∙ 08/22/2016

Lets keep it simple, Using simple architectures to outperform deeper and more complex architectures

Major winning Convolutional Neural Networks (CNNs), such as AlexNet, VGG...

0 Seyyed Hossein Hasanpour, et al. ∙

research

∙ 08/21/2016

STFCN: Spatio-Temporal FCN for Semantic Video Segmentation

This paper presents a novel method to involve both spatial and temporal ...

0 Mohsen Fayyaz, et al. ∙

research

∙ 05/30/2015

IDSA: Intelligent Distributed Sensor Activation Algorithm For Target Tracking With Wireless Sensor Network

One important application of the Wireless Sensor Network(WSN) is target ...

0 Mohammad Sabokrou, et al. ∙

research

∙ 05/29/2015

Feature Representation for Online Signature Verification

Biometrics systems have been used in a wide range of applications and ha...

0 Mohsen Fayyaz, et al. ∙

Mohammad Sabokrou

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