7 citations · 8 across the 11 of their papers we have counts for
12 papers
Learned Queries and Keys Are All You Need: Replacing the Value Projection with Structured Transforms
Ene Meco, Emadeldeen Hamdan, A. Enis Cetin
To reduce the number of parameters and cache memory requirements of transformers we introduce dual-headed transformers instead of three heads. We studied Walsh-Hadamard Transform (…
WHTMix: Efficient Stereo Depth Estimation via Walsh-Hadamard Token Mixing
Prathyush Sajith, Emadeldeen Hamdan, Ahmet Enis Cetin
Stereo depth estimation for driving, robotics and augmented reality must run at high resolution under tight latency budgets, yet in transformer-based matchers the global self-atten…
ShearFuse-UNet: Hadamard, DCT, and Shearlet Transform Fusion for Next-Day Wildfire Spread Prediction
Ene Meco, Yingyi Luo, Emadeldeen Hamdan +2
We propose ShearFuse-UNet, a lightweight and computationally efficient deep learning model for next-day wildfire spread prediction from multi-modal satellite data. The model integr…
A Large Scale Open-Source Image and Video Dataset for Robust Wildfire Detection and Classification
Emadeldeen Hamdan, Yingyi Luo, B. Ugur Toreyin +4
Wildfire detection and monitoring are critical for mitigating fire spread and reducing environmental and infrastructural damage. In this work, we introduce GWFP (Global Wildfire Pr…
Hybrid Multi-Dimensional MRI Prostate Cancer Detection via Hadamard Network-Based Bias Correction and Residual Networks
Emadeldeen Hamdan, Gorkem Durak, Muhammed Enes Tasci +7
Magnetic Resonance Imaging (MRI) is vital for prostate cancer (PCa) diagnosis. While advanced techniques such as Hybrid Multi-dimensional MRI (HM-MRI) have enhanced diagnostic capa…
Progressive Deep Learning for Automated Spheno-Occipital Synchondrosis Maturation Assessment
Omid Halimi Milani, Amanda Nikho, Marouane Tliba +4
Accurate assessment of spheno-occipital synchondrosis (SOS) maturation is a key indicator of craniofacial growth and a critical determinant for orthodontic and surgical timing. How…
Toward Generalizable Deep Learning Based Peatland Fire Detection via Walsh Hadamard Transform and Domain Adaptation
Emadeldeen Hamdan, Ahmad Faiz Tharima, Mohd Zahirasri Mohd Tohir +4
Machine learning-based wildfire detection has advanced significantly using deep learning models trained on large wildfire image and video datasets. However, peatland fires exhibit…
HTMA-Net: Towards Multiplication-Avoiding Neural Networks via Hadamard Transform and In-Memory Computing
Emadeldeen Hamdan, Ahmet Enis Cetin
Reducing the cost of multiplications is critical for efficient deep neural network deployment, especially in energy-constrained edge devices. In this work, we introduce HTMA-Net, a…
Sparse Mamba: Introducing Controllability, Observability, And Stability To Structural State Space Models
Emadeldeen Hamdan, Hongyi Pan, Ahmet Enis Cetin
Structured state space models' (SSMs) development in recent studies, such as Mamba and Mamba2, outperformed and solved the computational inefficiency of transformers and large lang…
Discrete Cosine Transform Based Decorrelated Attention for Vision Transformers
Hongyi Pan, Emadeldeen Hamdan, Xin Zhu +2
Self-attention is central to the success of Transformer architectures; however, learning the query, key, and value projections from random initialization remains challenging and co…
Wildfire Detection Via Transfer Learning: A Survey
Ziliang Hong, Emadeldeen Hamdan, Yifei Zhao +3
This paper surveys different publicly available neural network models used for detecting wildfires using regular visible-range cameras which are placed on hilltops or forest lookou…
Multichannel Orthogonal Transform-Based Perceptron Layers for Efficient ResNets
Hongyi Pan, Emadeldeen Hamdan, Xin Zhu +2
In this paper, we propose a set of transform-based neural network layers as an alternative to the Conv2D layers in Convolutional Neural Networks (CNNs). The proposed lay…