257 citations · 432 across the 14 of their papers we have counts for
16 papers
E-TCAV: Formalizing Penultimate Proxies for Efficient Concept Based Interpretability
Hasib Aslam, Muhammad Ali Chattha, Muhammad Taha Mukhtar +3
TCAV (Testing with Concept Activation Vectors) is an interpretability method that assesses the alignment between the internal representations of a trained neural network and human-…
SLUM-i: Semi-supervised Learning for Urban Mapping of Informal Settlements and Data Quality Benchmarking
Muhammad Taha Mukhtar, Syed Musa Ali Kazmi, Khola Naseem +5
Very-high-resolution remote-sensing imagery provides a scalable basis for delineating informal settlements, but sparse annotations, severe imbalance between informal-settlement and…
iBitter-Stack: A Multi-Representation Ensemble Learning Model for Accurate Bitter Peptide Identification
Sarfraz Ahmad, Momina Ahsan, Muhammad Nabeel Asim +2
The identification of bitter peptides is crucial in various domains, including food science, drug discovery, and biochemical research. These peptides not only contribute to the und…
A Perspective Analysis of Handwritten Signature Technology
Moises Diaz, Miguel A. Ferrer, Donato Impedovo +3
Handwritten signatures are biometric traits at the center of debate in the scientific community. Over the last 40 years, the interest in signature studies has grown steadily, havin…
Few-Shot Learning for Biometric Verification
Saad Bin Ahmed, Umaid M. Zaffar, Marium Aslam +1
In machine learning applications, it is common practice to feed as much information as possible. In most cases, the model can handle large data sets that allow to predict more accu…
KENN: Enhancing Deep Neural Networks by Leveraging Knowledge for Time Series Forecasting
Muhammad Ali Chattha, Ludger van Elst, Muhammad Imran Malik +2
End-to-end data-driven machine learning methods often have exuberant requirements in terms of quality and quantity of training data which are often impractical to fulfill in real-w…
ExAID: A Multimodal Explanation Framework for Computer-Aided Diagnosis of Skin Lesions
Adriano Lucieri, Muhammad Naseer Bajwa, Stephan Alexander Braun +3
One principal impediment in the successful deployment of AI-based Computer-Aided Diagnosis (CAD) systems in clinical workflows is their lack of transparent decision making. Althoug…
G1020: A Benchmark Retinal Fundus Image Dataset for Computer-Aided Glaucoma Detection
Muhammad Naseer Bajwa, Gur Amrit Pal Singh, Wolfgang Neumeier +3
Scarcity of large publicly available retinal fundus image datasets for automated glaucoma detection has been the bottleneck for successful application of artificial intelligence to…
Combining Fine- and Coarse-Grained Classifiers for Diabetic Retinopathy Detection
Muhammad Naseer Bajwa, Yoshinobu Taniguchi, Muhammad Imran Malik +3
Visual artefacts of early diabetic retinopathy in retinal fundus images are usually small in size, inconspicuous, and scattered all over retina. Detecting diabetic retinopathy requ…
Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Muhammad Naseer Bajwa, Muhammad Imran Malik, Shoaib Ahmed Siddiqui +4
With the advancement of powerful image processing and machine learning techniques, CAD has become ever more prevalent in all fields of medicine including ophthalmology. Since optic…
On Interpretability of Deep Learning based Skin Lesion Classifiers using Concept Activation Vectors
Adriano Lucieri, Muhammad Naseer Bajwa, Stephan Alexander Braun +3
Deep learning based medical image classifiers have shown remarkable prowess in various application areas like ophthalmology, dermatology, pathology, and radiology. However, the acc…
A Robust and Precise ConvNet for small non-coding RNA classification (RPC-snRC)
Muhammad Nabeel Asima, Muhammad Imran Malik, Andreas Dengela +1
Functional or non-coding RNAs are attracting more attention as they are now potentially considered valuable resources in the development of new drugs intended to cure several human…
A Robust Hybrid Approach for Textual Document Classification
Muhammad Nabeel Asim, Muhammad Usman Ghani Khan, Muhammad Imran Malik +2
Text document classification is an important task for diverse natural language processing based applications. Traditional machine learning approaches mainly focused on reducing dim…
KINN: Incorporating Expert Knowledge in Neural Networks
Muhammad Ali Chattha, Shoaib Ahmed Siddiqui, Muhammad Imran Malik +3
The promise of ANNs to automatically discover and extract useful features/patterns from data without dwelling on domain expertise although seems highly promising but comes at the c…
AirScript - Creating Documents in Air
Ayushman Dash, Amit Sahu, Rajveer Shringi +5
This paper presents a novel approach, called AirScript, for creating, recognizing and visualizing documents in air. We present a novel algorithm, called 2-DifViz, that converts the…
A Generic Method for Automatic Ground Truth Generation of Camera-captured Documents
Sheraz Ahmed, Muhammad Imran Malik, Muhammad Zeshan Afzal +4
The contribution of this paper is fourfold. The first contribution is a novel, generic method for automatic ground truth generation of camera-captured document images (books, magaz…