Search Results for author: Ghulam Rasool

Found 18 papers, 3 papers with code

Exploring Robust Architectures for Deep Artificial Neural Networks

1 code implementation30 Jun 2021 Asim Waqas, Ghulam Rasool, Hamza Farooq, Nidhal C. Bouaynaya

The architectures of deep artificial neural networks (DANNs) are routinely studied to improve their predictive performance.

Image Classification Neural Architecture Search +1

Building Flexible, Scalable, and Machine Learning-ready Multimodal Oncology Datasets

1 code implementation30 Sep 2023 Aakash Tripathi, Asim Waqas, Kavya Venkatesan, Yasin Yilmaz, Ghulam Rasool

The advancements in data acquisition, storage, and processing techniques have resulted in the rapid growth of heterogeneous medical data.

Data Integration

Revisiting the Fragility of Influence Functions

1 code implementation22 Mar 2023 Jacob R. Epifano, Ravi P. Ramachandran, Aaron J. Masino, Ghulam Rasool

In the last few years, many works have tried to explain the predictions of deep learning models.

Constrained State Estimation -- A Review

no code implementations10 Jul 2018 Nesrine Amor, Ghulam Rasool, Nidhal C. Bouaynaya

The real-world applications in signal processing generally involve estimating the system state or parameters in nonlinear, non-Gaussian dynamic systems.

Robust Explainability: A Tutorial on Gradient-Based Attribution Methods for Deep Neural Networks

no code implementations23 Jul 2021 Ian E. Nielsen, Dimah Dera, Ghulam Rasool, Nidhal Bouaynaya, Ravi P. Ramachandran

Later, we discuss how gradient-based methods can be evaluated for their robustness and the role that adversarial robustness plays in having meaningful explanations.

Adversarial Robustness

Dilated Inception U-Net (DIU-Net) for Brain Tumor Segmentation

no code implementations15 Aug 2021 Daniel E. Cahall, Ghulam Rasool, Nidhal C. Bouaynaya, Hassan M. Fathallah-Shaykh

Magnetic resonance imaging (MRI) is routinely used for brain tumor diagnosis, treatment planning, and post-treatment surveillance.

Brain Tumor Segmentation Segmentation +1

Self-Compression in Bayesian Neural Networks

no code implementations10 Nov 2021 Giuseppina Carannante, Dimah Dera, Ghulam Rasool, Nidhal C. Bouaynaya

We show that Bayesian neural networks automatically discover redundancy in model parameters, thus enabling self-compression, which is linked to the propagation of uncertainty through the layers of the network.

BIG-bench Machine Learning

SUPER-Net: Trustworthy Medical Image Segmentation with Uncertainty Propagation in Encoder-Decoder Networks

no code implementations10 Nov 2021 Giuseppina Carannante, Dimah Dera, Nidhal C. Bouaynaya, Hassan M. Fathallah-Shaykh, Ghulam Rasool

Moreover, the uncertainty map of the proposed SUPER-Net associates low confidence (or equivalently high uncertainty) to patches in the test input images that are corrupted with noise, artifacts, or adversarial attacks.

Image Segmentation Medical Image Segmentation +3

Transformers in Time-series Analysis: A Tutorial

no code implementations28 Apr 2022 Sabeen Ahmed, Ian E. Nielsen, Aakash Tripathi, Shamoon Siddiqui, Ghulam Rasool, Ravi P. Ramachandran

Transformer architecture has widespread applications, particularly in Natural Language Processing and computer vision.

Time Series Time Series Analysis

Multimodal Data Integration for Oncology in the Era of Deep Neural Networks: A Review

no code implementations11 Mar 2023 Asim Waqas, Aakash Tripathi, Ravi P. Ramachandran, Paul Stewart, Ghulam Rasool

Recent deep learning frameworks such as Graph Neural Networks (GNNs) and Transformers have shown remarkable success in multimodal learning.

Data Integration

EvalAttAI: A Holistic Approach to Evaluating Attribution Maps in Robust and Non-Robust Models

no code implementations15 Mar 2023 Ian E. Nielsen, Ravi P. Ramachandran, Nidhal Bouaynaya, Hassan M. Fathallah-Shaykh, Ghulam Rasool

The expansion of explainable artificial intelligence as a field of research has generated numerous methods of visualizing and understanding the black box of a machine learning model.

Explainable artificial intelligence

Targeted Background Removal Creates Interpretable Feature Visualizations

no code implementations22 Jun 2023 Ian E. Nielsen, Erik Grundeland, Joseph Snedeker, Ghulam Rasool, Ravi P. Ramachandran

Feature visualization is used to visualize learned features for black box machine learning models.

Deep Ensemble for Rotorcraft Attitude Prediction

no code implementations29 Jun 2023 Hikmat Khan, Nidhal Carla Bouaynaya, Ghulam Rasool, Tyler Travis, Lacey Thompson, Charles C. Johnson

Our recent work demonstrated that AI algorithms could use video data from onboard cameras and correctly identify different flight parameters from cockpit gauges, e. g., indicated airspeed.

Variational Density Propagation Continual Learning

no code implementations22 Aug 2023 Christopher Angelini, Nidhal Bouaynaya, Ghulam Rasool

Catastrophic forgetting is mitigated by using the closed-form ELBO to approximate the Minimum Description Length (MDL) Principle, inherently penalizing changes in the model likelihood by minimizing the KL Divergence between the variational posterior for the current task and the previous task's variational posterior acting as the prior.

Bayesian Inference Continual Learning +2

Deployment of a Robust and Explainable Mortality Prediction Model: The COVID-19 Pandemic and Beyond

no code implementations28 Nov 2023 Jacob R. Epifano, Stephen Glass, Ravi P. Ramachandran, Sharad Patel, Aaron J. Masino, Ghulam Rasool

This study investigated the performance, explainability, and robustness of deployed artificial intelligence (AI) models in predicting mortality during the COVID-19 pandemic and beyond.

Mortality Prediction

Vision-Language Models for Medical Report Generation and Visual Question Answering: A Review

no code implementations4 Mar 2024 Iryna Hartsock, Ghulam Rasool

Our paper reviews recent advancements in developing VLMs specialized for healthcare, focusing on models designed for medical report generation and visual question answering.

Medical Report Generation Question Answering +1

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