94 citations · 397 across the 13 of their papers we have counts for
16 papers
TabAug: Data Driven Augmentation for Enhanced Table Structure Recognition
Umar Khan, Sohaib Zahid, Muhammad Asad Ali +2
Table Structure Recognition is an essential part of end-to-end tabular data extraction in document images. The recent success of deep learning model architectures in computer visio…
Short-Term Load Forecasting using Bi-directional Sequential Models and Feature Engineering for Small Datasets
Abdul Wahab, Muhammad Anas Tahir, Naveed Iqbal +2
Electricity load forecasting enables the grid operators to optimally implement the smart grid's most essential features such as demand response and energy efficiency. Electricity d…
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…
Table Structure Extraction with Bi-directional Gated Recurrent Unit Networks
Saqib Ali Khan, Syed Muhammad Daniyal Khalid, Muhammad Ali Shahzad +1
Tables present summarized and structured information to the reader, which makes table structure extraction an important part of document understanding applications. However, table…
Do Cross Modal Systems Leverage Semantic Relationships?
Shah Nawaz, Muhammad Kamran Janjua, Ignazio Gallo +3
Current cross-modal retrieval systems are evaluated using R@K measure which does not leverage semantic relationships rather strictly follows the manually marked image text query pa…
An Open-World Extension to Knowledge Graph Completion Models
Haseeb Shah, Johannes Villmow, Adrian Ulges +2
We present a novel extension to embedding-based knowledge graph completion models which enables them to perform open-world link prediction, i.e. to predict facts for entities unsee…
Rethinking Table Recognition using Graph Neural Networks
Shah Rukh Qasim, Hassan Mahmood, Faisal Shafait
Document structure analysis, such as zone segmentation and table recognition, is a complex problem in document processing and is an active area of research. The recent success of d…
Converting a Common Document Scanner to a Multispectral Scanner
Zohaib Khan, Faisal Shafait, Ajmal Mian
We propose the construction of a prototype scanner designed to capture multispectral images of documents. A standard sheet-feed scanner is modified by disconnecting its internal li…
Distillation Techniques for Pseudo-rehearsal Based Incremental Learning
Haseeb Shah, Khurram Javed, Faisal Shafait
The ability to learn from incrementally arriving data is essential for any life-long learning system. However, standard deep neural networks forget the knowledge about the old task…
Revisiting Distillation and Incremental Classifier Learning
Khurram Javed, Faisal Shafait
One of the key differences between the learning mechanism of humans and Artificial Neural Networks (ANNs) is the ability of humans to learn one task at a time. ANNs, on the other h…
Efficient Estimation of k for the Nearest Neighbors Class of Methods
Aleksander Lodwich, Faisal Shafait, Thomas Breuel
The k Nearest Neighbors (kNN) method has received much attention in the past decades, where some theoretical bounds on its performance were identified and where practical optimizat…
Sparseness helps: Sparsity Augmented Collaborative Representation for Classification
Naveed Akhtar, Faisal Shafait, Ajmal Mian
Many classification approaches first represent a test sample using the training samples of all the classes. This collaborative representation is then used to label the test sample.…
Representation Learning with Deep Extreme Learning Machines for Efficient Image Set Classification
Muhammad Uzair, Faisal Shafait, Bernard Ghanem +1
Efficient and accurate joint representation of a collection of images, that belong to the same class, is a major research challenge for practical image set classification. Existing…
Discriminative Bayesian Dictionary Learning for Classification
Naveed Akhtar, Faisal Shafait, Ajmal Mian
We propose a Bayesian approach to learn discriminative dictionaries for sparse representation of data. The proposed approach infers probability distributions over the atoms of a di…
Dense 3D Face Correspondence
Syed Zulqarnain Gilani, Ajmal Mian, Faisal Shafait +1
We present an algorithm that automatically establishes dense correspondences between a large number of 3D faces. Starting from automatically detected sparse correspondences on the…
Multispectral Palmprint Encoding and Recognition
Zohaib Khan, Faisal Shafait, Yiqun Hu +1
Palmprints are emerging as a new entity in multi-modal biometrics for human identification and verification. Multispectral palmprint images captured in the visible and infrared spe…