Search Results - "Khan, Sultan Daud"

An Encoder–Decoder Deep Learning Framework for Building Footprints Extraction from Aerial Imagery by Khan, Sultan Daud, Alarabi, Louai, Basalamah, Saleh

“…Building footprints segmentation in high-resolution satellite images has wide range of applications in disaster management, land cover analysis and urban…”
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Multi-Branch Deep Learning Framework for Land Scene Classification in Satellite Imagery by Khan, Sultan Daud, Basalamah, Saleh

“…Land scene classification in satellite imagery has a wide range of applications in remote surveillance, environment monitoring, remote scene analysis, Earth…”
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Multi-Scale and Context-Aware Framework for Flood Segmentation in Post-Disaster High Resolution Aerial Images by Khan, Sultan Daud, Basalamah, Saleh

“…Floods are the most frequent natural disasters, occurring almost every year around the globe. To mitigate the damage caused by a flood, it is important to…”
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A study on detecting drones using deep convolutional neural networks by Saqib, Muhammad, Daud Khan, Sultan, Sharma, Nabin, Blumenstein, Michael

“…The object detection is a challenging problem in computer vision with various potential real-world applications. The objective of this study is to evaluate the…”
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Sparse to Dense Scale Prediction for Crowd Couting in High Density Crowds by Khan, Sultan Daud, Basalamah, Saleh

“…Head detection-based crowd counting is of great importance and serves as a preprocessing step in many visual applications, for example, counting, tracking, and…”
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Scale Driven Convolutional Neural Network Model for People Counting and Localization in Crowd Scenes by Basalamah, Saleh, Khan, Sultan Daud, Ullah, Habib

“…Counting and localization of people in videos consisting of low density to high density crowds encounter many key challenges including complex backgrounds,…”
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Weed–Crop Segmentation in Drone Images with a Novel Encoder–Decoder Framework Enhanced via Attention Modules by Khan, Sultan Daud, Basalamah, Saleh, Lbath, Ahmed

“…The rapid expansion of the world’s population has resulted in an increased demand for agricultural products which necessitates the need to improve crop yields…”
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A Unified Deep Learning Framework of Multi-scale Detectors for Geo-spatial Object Detection in High-Resolution Satellite Images by Khan, Sultan Daud, Alarabi, Louai, Basalamah, Saleh

“…Geo-spatial object detection in high-resolution satellite images has many applications in urban planning, military applications, maritime surveillance,…”
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A Novel Detection Refinement Technique for Accurate Identification of Nephrops norvegicus Burrows in Underwater Imagery by Naseer, Atif, Baro, Enrique Nava, Khan, Sultan Daud, Vila, Yolanda

“…With the evolution of the convolutional neural network (CNN), object detection in the underwater environment has gained a lot of attention. However, due to the…”
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DSMSA-Net: Deep Spatial and Multi-scale Attention Network for Road Extraction in High Spatial Resolution Satellite Images by Khan, Sultan Daud, Alarabi, Louai, Basalamah, Saleh

“…Road segmentation in high spatial resolution satellite images is an important research topic and has numerous applications in traffic monitoring and…”
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Internal Emotion Classification Using EEG Signal With Sparse Discriminative Ensemble by Ullah, Habib, Uzair, Muhammad, Mahmood, Arif, Ullah, Mohib, Khan, Sultan Daud, Cheikh, Faouzi Alaya

“…Among various physiological signal acquisition methods for the study of the human brain, EEG (Electroencephalography) is more effective. EEG provides a…”
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Multi-Scale Person Localization With Multi-Stage Deep Sequential Framework by Khan, Sultan Daud, Basalamah, Saleh

“…Person detection in real videos and images is a classical research problem in computer vision. Person detection is a nontrivial problem that offers many…”
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Toward Smart Lockdown: A Novel Approach for COVID-19 Hotspots Prediction Using a Deep Hybrid Neural Network by Khan, Sultan Daud, Alarabi, Louai, Basalamah, Saleh

“…COVID-19 caused the largest economic recession in the history by placing more than one third of world’s population in lockdown. The prolonged restrictions on…”
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Deep Hybrid Network for Land Cover Semantic Segmentation in High-Spatial Resolution Satellite Images by Khan, Sultan Daud, Alarabi, Louai, Basalamah, Saleh

“…Land cover semantic segmentation in high-spatial resolution satellite images plays a vital role in efficient management of land resources, smart agriculture,…”
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Multi-feature-based crowd video modeling for visual event detection by Ullah, Habib, Islam, Ihtesham Ul, Ullah, Mohib, Afaq, Muhammad, Khan, Sultan Daud, Iqbal, Javed

“…We propose a novel method for modeling crowd video dynamics by adopting a two-stream convolutional architecture which incorporates spatial and temporal…”
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Crowd Counting in Low-Resolution Crowded Scenes Using Region-Based Deep Convolutional Neural Networks by Saqib, Muhammad, Khan, Sultan Daud, Sharma, Nabin, Blumenstein, Michael

“…Crowd counting and density estimation is an important and challenging problem in the visual analysis of the crowd. Most of the existing approaches use…”
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Indoor Scene Classification through Dual-Stream Deep Learning: A Framework for Improved Scene Understanding in Robotics by Khan, Sultan Daud, Othman, Kamal M.

“…Indoor scene classification plays a pivotal role in enabling social robots to seamlessly adapt to their environments, facilitating effective navigation and…”
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Efficient broadband light absorption in thin-film a-Si solar cell based on double sided hybrid bi-metallic nanogratings by Subhan, Fazal E, Khan, Aimal Daud, Hilal, Fazal E, Khan, Adnan Daud, Khan, Sultan Daud, Ullah, Rehan, Imran, Muhammad, Noman, Muhammad

“…Thin film solar cells (TFSCs) suffer from poor light absorption due to their small thickness, which limits most of their practical applications. Surface…”
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Crowd Counting in Diverse Environments Using a Deep Routing Mechanism Informed by Crowd Density Levels by Alhawsawi, Abdullah N, Khan, Sultan Daud, Ur Rehman, Faizan

“…Automated crowd counting is a crucial aspect of surveillance, especially in the context of mass events attended by large populations. Traditional methods of…”
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Deep learning framework for congestion detection at public places via learning from synthetic data by Basalamah, Saleh, Khan, Sultan Daud, Felemban, Emad, Naseer, Atif, Rehman, Faizan Ur

“…Congestion in public places is one of the major problems in public transportation systems and causes a high level of discomfort for the commuters…”
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