25 citations · 53 across the 7 of their papers we have counts for
7 papers
Quality Scalable Quantization Methodology for Deep Learning on Edge
Salman Abdul Khaliq, Rehan Hafiz
Deep Learning Architectures employ heavy computations and bulk of the computational energy is taken up by the convolution operations in the Convolutional Neural Networks. The objec…
Inferior Myocardial Infarction Detection from lead II of ECG: A Gramian Angular Field-based 2D-CNN Approach
Asim Yousuf, Rehan Hafiz, Saqib Riaz +3
This paper presents a novel method for inferior myocardial infarction (MI) detection using lead II of electrocardiogram (ECG). We evaluate our proposed method on a public dataset,…
Distribution Regularized Self-Supervised Learning for Domain Adaptation of Semantic Segmentation
Javed Iqbal, Hamza Rawal, Rehan Hafiz +2
This paper proposes a novel pixel-level distribution regularization scheme (DRSL) for self-supervised domain adaptation of semantic segmentation. In a typical setting, the classifi…
FogAdapt: Self-Supervised Domain Adaptation for Semantic Segmentation of Foggy Images
Javed Iqbal, Rehan Hafiz, Mohsen Ali
This paper presents FogAdapt, a novel approach for domain adaptation of semantic segmentation for dense foggy scenes. Although significant research has been directed to reduce the…
MAQ-CaF: A Modular Air Quality Calibration and Forecasting method for cross-sensitive pollutants
Yousuf Hashmy, ZillUllah Khan, Rehan Hafiz +2
The climatic challenges are rising across the globe in general and in worst hit under-developed countries in particular. The need for accurate measurements and forecasting of pollu…
Systimator: A Design Space Exploration Methodology for Systolic Array based CNNs Acceleration on the FPGA-based Edge Nodes
Hazoor Ahmad, Muhammad Tanvir, Muhammad Abdullah Hanif +3
The evolution of IoT based smart applications demand porting of artificial intelligence algorithms to the edge computing devices. CNNs form a large part of these AI algorithms. Sys…
MPNA: A Massively-Parallel Neural Array Accelerator with Dataflow Optimization for Convolutional Neural Networks
Muhammad Abdullah Hanif, Rachmad Vidya Wicaksana Putra, Muhammad Tanvir +3
The state-of-the-art accelerators for Convolutional Neural Networks (CNNs) typically focus on accelerating only the convolutional layers, but do not prioritize the fully-connected…