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How has Hayat Ullah's publication output changed over time?
ScholarIQpublication output · 2020–2024
Output grew0% over the shown period — from 1 works in 2020 to 1 in 2024.
1
4
2
2
1
20202021202220232024
What are the most-cited papers on Hayat Ullah?
ScholarIQmost cited works
Automatic Detection of Citrus Fruit and Leaves Diseases Using Deep Neural Network Model
Asad Masood Khattak, Muhammad Usama Asghar, Ulfat Batool, Muhammad Zubair Asghar, Hayat Ullah, Mabrook Al‐Rakhami, Abdu Gumaei
IEEE Access. 2021240 CitationsOPEN ACCESS
Light-DehazeNet: A Novel Lightweight CNN Architecture for Single Image Dehazing
Hayat Ullah, Khan Muhammad, Muhammad Irfan, Saeed Anwar, Muhammad Sajjad, Ali Shariq Imran, Victor Hugo C. de Albuquerque
S4210173141. 2021213 Citations
Vision-Based Semantic Segmentation in Scene Understanding for Autonomous Driving: Recent Achievements, Challenges, and Outlooks
Khan Muhammad, Tanveer Hussain, Hayat Ullah, Javier Del Ser, Mahdi Rezaei, Neeraj Kumar, Mohammad Hijji, Paolo Bellavista, Victor Hugo C. de Albuquerque
S144771191. 2022201 CitationsOPEN ACCESS
Efficient Detection of DDoS Attacks Using a Hybrid Deep Learning Model with Improved Feature Selection
Daniyal Alghazzawi, Omaimah Bamasag, Hayat Ullah, Muhammad Zubair Asghar
Applied Sciences. 2021140 CitationsOPEN ACCESS
ViT-ReT: Vision and Recurrent Transformer Neural Networks for Human Activity Recognition in Videos
James Wensel, Hayat Ullah, Arslan Munir
IEEE Access. 202382 CitationsOPEN ACCESS
Related on ScholarIQ
Florida Atlantic University
Institution
Automatic Detection of Citrus Fruit and Leaves Diseases Using Deep Neural Network Model
Paper
Light-DehazeNet: A Novel Lightweight CNN Architecture for Single Image Dehazing
Paper
Vision-Based Semantic Segmentation in Scene Understanding for Autonomous Driving: Recent Achievements, Challenges, and Outlooks
Paper
Efficient Detection of DDoS Attacks Using a Hybrid Deep Learning Model with Improved Feature Selection
Paper
ViT-ReT: Vision and Recurrent Transformer Neural Networks for Human Activity Recognition in Videos
Paper