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07/04/2023
Mitigating Bias: Enhancing Image Classification by Improving Model Explanations
Deep learning models have demonstrated remarkable capabilities in learni...
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06/27/2023
IMPOSITION: Implicit Backdoor Attack through Scenario Injection
This paper presents a novel backdoor attack called IMPlicit BackdOor Att...
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06/14/2023
Global-Local Processing in Convolutional Neural Networks
Convolutional Neural Networks (CNNs) have achieved outstanding performan...
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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...
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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...
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05/30/2023
Quantifying Overfitting: Evaluating Neural Network Performance through Analysis of Null Space
Machine learning models that are overfitted/overtrained are more vulnera...
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11/20/2022
Are Out-of-Distribution Detection Methods Reliable?
This paper establishes a novel evaluation framework for assessing the pe...
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07/22/2022
MobileDenseNet: A new approach to object detection on mobile devices
Object detection problem solving has developed greatly within the past f...
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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,...
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01/31/2022
Deep-Disaster: Unsupervised Disaster Detection and Localization Using Visual Data
Social media plays a significant role in sharing essential information, ...
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01/05/2022
All You Need In Sign Language Production
Sign Language is the dominant form of communication language used in the...
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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...
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09/02/2021
Multi-Modal Zero-Shot Sign Language Recognition
Zero-Shot Learning (ZSL) has rapidly advanced in recent years. Towards o...
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03/29/2021
Sign Language Production: A Review
Sign Language is the dominant yet non-primary form of communication lang...
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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...
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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...
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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...
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03/02/2021
Image/Video Deep Anomaly Detection: A Survey
The considerable significance of Anomaly Detection (AD) problem has rece...
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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...
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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...
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06/20/2020
G2D: Generate to Detect Anomalies
In this paper, we propose a novel method for irregularity detection. Pre...
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06/20/2020
G2D: Generate to Detect Anomaly
In this paper, we propose a novel method for irregularity detection. Pre...
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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...
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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...
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11/08/2019
AutoIDS: Auto-encoder Based Method for Intrusion Detection System
Intrusion Detection System (IDS) is one of the most effective solutions ...
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08/27/2019
Self-Supervised Representation Learning via Neighborhood-Relational Encoding
In this paper, we propose a novel self-supervised representation learnin...
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07/12/2019
AVD: Adversarial Video Distillation
In this paper, we present a simple yet efficient approach for video repr...
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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...
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06/24/2018
Online Signature Verification using Deep Representation: A new Descriptor
This paper presents an accurate method for verifying online signatures. ...
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06/16/2018
Semantic Video Segmentation: A Review on Recent Approaches
This paper gives an overview on semantic segmentation consists of an exp...
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05/24/2018
AVID: Adversarial Visual Irregularity Detection
Real-time detection of irregularities in visual data is very invaluable ...
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02/25/2018
Adversarially Learned One-Class Classifier for Novelty Detection
Novelty detection is the process of identifying the observation(s) that ...
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02/17/2018
Towards Principled Design of Deep Convolutional Networks: Introducing SimpNet
Major winning Convolutional Neural Networks (CNNs), such as VGGNet, ResN...
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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 ...
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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...
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08/21/2016
STFCN: Spatio-Temporal FCN for Semantic Video Segmentation
This paper presents a novel method to involve both spatial and temporal ...
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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 ...
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05/29/2015