28 citations · 108 across the 15 of their papers we have counts for
16 papers
On the Value of Labeled Data and Symbolic Methods for Hidden Neuron Activation Analysis
Abhilekha Dalal, Rushrukh Rayan, Adrita Barua +3
A major challenge in Explainable AI is in correctly interpreting activations of hidden neurons: accurate interpretations would help answer the question of what a deep learning syst…
Advancements in Generative AI: A Comprehensive Review of GANs, GPT, Autoencoders, Diffusion Model, and Transformers
Staphord Bengesi, Hoda El-Sayed, Md Kamruzzaman Sarker +3
The launch of ChatGPT has garnered global attention, marking a significant milestone in the field of Generative Artificial Intelligence. While Generative AI has been in effect for…
Understanding CNN Hidden Neuron Activations Using Structured Background Knowledge and Deductive Reasoning
Abhilekha Dalal, Md Kamruzzaman Sarker, Adrita Barua +2
A major challenge in Explainable AI is in correctly interpreting activations of hidden neurons: accurate interpretations would provide insights into the question of what a deep lea…
Explaining Deep Learning Hidden Neuron Activations using Concept Induction
Abhilekha Dalal, Md Kamruzzaman Sarker, Adrita Barua +1
One of the current key challenges in Explainable AI is in correctly interpreting activations of hidden neurons. It seems evident that accurate interpretations thereof would provide…
A Low-cost Humanoid Prototype Intended to assist people with disability using Raspberry Pi
Md. Nayem Hasan Muntasir, Tariqul Islam Siam, Md. Kamruzzaman Sarker
This paper will try to delineate the making of a Humanoid prototype intended to assist people with disability (PWD). The assistance that this prototype will offer is rather rudimen…
Towards Human-Compatible XAI: Explaining Data Differentials with Concept Induction over Background Knowledge
Cara Widmer, Md Kamruzzaman Sarker, Srikanth Nadella +6
Concept induction, which is based on formal logical reasoning over description logics, has been used in ontology engineering in order to create ontology (TBox) axioms from the base…
Neuro-Symbolic Artificial Intelligence: Current Trends
Md Kamruzzaman Sarker, Lu Zhou, Aaron Eberhart +1
Neuro-Symbolic Artificial Intelligence -- the combination of symbolic methods with methods that are based on artificial neural networks -- has a long-standing history. In this arti…
Neural Fuzzy Extractors: A Secure Way to Use Artificial Neural Networks for Biometric User Authentication
Abhishek Jana, Bipin Paudel, Md Kamruzzaman Sarker +3
Powered by new advances in sensor development and artificial intelligence, the decreasing cost of computation, and the pervasiveness of handheld computation devices, biometric user…
Efficient Concept Induction for Description Logics
Md Kamruzzaman Sarker, Pascal Hitzler
Concept Induction refers to the problem of creating complex Description Logic class descriptions (i.e., TBox axioms) from instance examples (i.e., ABox data). In this paper we look…
Reasoning over RDF Knowledge Bases using Deep Learning
Monireh Ebrahimi, Md Kamruzzaman Sarker, Federico Bianchi +3
Semantic Web knowledge representation standards, and in particular RDF and OWL, often come endowed with a formal semantics which is considered to be of fundamental importance for t…
Rule-based OWL Modeling with ROWLTab Protege Plugin
Md. Kamruzzaman Sarker, Adila Krisnadhi, David Carral +1
It has been argued that it is much easier to convey logical statements using rules rather than OWL (or description logic (DL)) axioms. Based on recent theoretical developments on t…
OWLAx: A Protege Plugin to Support Ontology Axiomatization through Diagramming
Md. Kamruzzaman Sarker, Adila A. Krisnadhi, Pascal Hitzler
Once the conceptual overview, in terms of a somewhat informal class diagram, has been designed in the course of engineering an ontology, the process of adding many of the appropria…
Modeling OWL with Rules: The ROWL Protege Plugin
Md. Kamruzzaman Sarker, David Carral, Adila A. Krisnadhi +1
In our experience, some ontology users find it much easier to convey logical statements using rules rather than OWL (or description logic) axioms. Based on recent theoretical devel…
Emotion Recognition from Speech based on Relevant Feature and Majority Voting
Md. Kamruzzaman Sarker, Kazi Md. Rokibul Alam, Md. Arifuzzaman
This paper proposes an approach to detect emotion from human speech employing majority voting technique over several machine learning techniques. The contribution of this work is i…
Relating Input Concepts to Convolutional Neural Network Decisions
Ning Xie, Md Kamruzzaman Sarker, Derek Doran +2
Many current methods to interpret convolutional neural networks (CNNs) use visualization techniques and words to highlight concepts of the input seemingly relevant to a CNN's decis…
Explaining Trained Neural Networks with Semantic Web Technologies: First Steps
Md Kamruzzaman Sarker, Ning Xie, Derek Doran +2
The ever increasing prevalence of publicly available structured data on the World Wide Web enables new applications in a variety of domains. In this paper, we provide a conceptual…