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Amin Ullah - IEEE Xplore Author Profile
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Amin Ullah

Publications
20
Citations
1,790
Publications by Year
20182024
Co-Authors:
Show All Co-Authors (41)
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Amin Ullah

Affiliation

Collaborative Robotics and Intelligent Systems (CoRIS) Institute
Oregon State University
OR, United States

Publication Topics

Biography

Amin Ullah (Member, IEEE) received the Ph.D. degree in digital contents from Sejong University, Seoul, South Korea, in 2021.,He is currently working as a Postdoctoral Researcher with the CoRIS Institute, Oregon State University, Corvallis, OR, USA. He has published 40+ scientific articles in reputed peer reviewed international journals and conferences, including IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Informatics, IEEE Transactions on Intelligent Transportation Systems, IEEE Internet of Things Journal, IEEE Access, Future Generation Computer Systems (Elsevier), Applied Soft Computing (Elsevier), International Journal of Intelligent Systems, Multimedia Tools and Applications (Springer), Mobile Networks an...
Publications
20
Citations
1,790
Publications by Year
20182024
Co-Authors:
Show All Co-Authors (41)
Author's Published Works

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CVAE-SM: A Conditional Variational Autoencoder with Style Modulation for Efficient Uncertainty Quantification

Amin Ullah;Taiqing Yan;Li Fuxin

2024 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2024 | Conference Paper |
Deep learning has brought transformative advancements to object segmentation, especially in marine robotics contexts such as waste management and subaquatic infrastructure oversight. However, a central challenge persists: calibrating the prediction confidence of the model to ensure robust and reliable outcomes, especially within the demanding underwater environment. Existing solutions for estimati...Show More

CVAE-SM: A Conditional Variational Autoencoder with Style Modulation for Efficient Uncertainty Quantification

Amin Ullah;Taiqing Yan;Li Fuxin

Year: 2024 | Conference Paper |

Fine-Tuned training method for semantic text similarity measurement using SBERT, Bi-LSTM and Attention Network

Zafar Ali;Abdul Aziz;Asad Ali;Amin Ullah;Muhammad Aurangzeb;Muhammad Ahsan Nazir

2023 International Conference on Machine Vision, Image Processing and Imaging Technology (MVIPIT)
Year: 2023 | Conference Paper |
The Semantic Textual Similarity (STS) problem measures the degree to which two text fragments are similar. In QA systems, it is a crucial tool for extracting useful information from documents. In STS challenges, optimizing lexical gaps between phrases has been a crucial issue. Text similarity may be affected by the distance between major parts of the sentence and the absence of context in the text...Show More

Fine-Tuned training method for semantic text similarity measurement using SBERT, Bi-LSTM and Attention Network

Zafar Ali;Abdul Aziz;Asad Ali;Amin Ullah;Muhammad Aurangzeb;Muhammad Ahsan Nazir

Year: 2023 | Conference Paper |

Efficient Person Reidentification for IoT-Assisted Cyber–Physical Systems

Samee Ullah Khan;Ijaz Ul Haq;Noman Khan;Amin Ullah;Khan Muhammad;Huiling Chen;Sung Wook Baik;Victor Hugo C. de Albuquerque

IEEE Internet of Things Journal
Year: 2023 | Volume: 10, Issue: 21 | Journal Article |
Cited by: Papers (5)
The main objective of this study is to propose a cyber–physical system (CPS)-based person reidentification (P-ReID) framework for smart surveillance. The Internet of Things (IoT)-based interconnected vision sensors in smart cities are considered essential elements of a CPS, and contribute significantly to urban security. However, the reidentification of targeted persons using emerging edge AI tech...Show More

Efficient Person Reidentification for IoT-Assisted Cyber–Physical Systems

Samee Ullah Khan;Ijaz Ul Haq;Noman Khan;Amin Ullah;Khan Muhammad;Huiling Chen;Sung Wook Baik;Victor Hugo C. de Albuquerque

Year: 2023 | Volume: 10, Issue: 21 | Journal Article |

Deep Learning Assists Surveillance Experts: Toward Video Data Prioritization

Tanveer Hussain;Fath U Min Ullah;Samee Ullah Khan;Amin Ullah;Umair Haroon;Khan Muhammad;Sung Wook Baik;Victor Hugo C. de Albuquerque

IEEE Transactions on Industrial Informatics
Year: 2023 | Volume: 19, Issue: 7 | Journal Article |
Video summarization (VS) suppresses high-dimensional (HD) video data by only extracting the important information. However, prior research has not focused on the need for surveillance VS, that is used for many applications to assist video surveillance experts, including video retrieval and data storage. In addition, mainstream techniques commonly use two-dimensional (2-D) deep models for VS, ignor...Show More

Deep Learning Assists Surveillance Experts: Toward Video Data Prioritization

Tanveer Hussain;Fath U Min Ullah;Samee Ullah Khan;Amin Ullah;Umair Haroon;Khan Muhammad;Sung Wook Baik;Victor Hugo C. de Albuquerque

Year: 2023 | Volume: 19, Issue: 7 | Journal Article |

LocateUAV: Unmanned Aerial Vehicle Location Estimation via Contextual Analysis in an IoT Environment

Naqqash Dilshad;Amin Ullah;Jaeho Kim;Jeongwook Seo

IEEE Internet of Things Journal
Year: 2023 | Volume: 10, Issue: 5 | Journal Article |
Cited by: Papers (20)
Object detection supported by unmanned aerial vehicles (UAVs) has generated significant interest in recent years including applications, such as surveillance, search for missing persons, traffic, and disaster management. Location awareness is a challenging task, particularly, the deployment of UAVs in a global positioning system (GPS) restricted environment or GPS sensor failure. To mitigate this ...Show More

LocateUAV: Unmanned Aerial Vehicle Location Estimation via Contextual Analysis in an IoT Environment

Naqqash Dilshad;Amin Ullah;Jaeho Kim;Jeongwook Seo

Year: 2023 | Volume: 10, Issue: 5 | Journal Article |

AI-Driven Salient Soccer Events Recognition Framework for Next-Generation IoT-Enabled Environments

Khan Muhammad;Hayat Ullah;Mohammad S. Obaidat;Amin Ullah;Arslan Munir;Muhammad Sajjad;Victor Hugo C. de Albuquerque

IEEE Internet of Things Journal
Year: 2023 | Volume: 10, Issue: 3 | Journal Article |
Cited by: Papers (12)
The salient event recognition of soccer matches in the next-generation Internet of Things (Nx-IoT) environment aims to analyze the performance of players/teams by the sports analytics and managerial staff. The embedded Nx-IoT devices carried by the soccer players during the match capture and transmit data to an artificial intelligence (AI)-assisted computing platform. The interconnectivity of data...Show More

AI-Driven Salient Soccer Events Recognition Framework for Next-Generation IoT-Enabled Environments

Khan Muhammad;Hayat Ullah;Mohammad S. Obaidat;Amin Ullah;Arslan Munir;Muhammad Sajjad;Victor Hugo C. de Albuquerque

Year: 2023 | Volume: 10, Issue: 3 | Journal Article |

A Multi-Stream Sequence Learning Framework for Human Interaction Recognition

Umair Haroon;Amin Ullah;Tanveer Hussain;Waseem Ullah;Muhammad Sajjad;Khan Muhammad;Mi Young Lee;Sung Wook Baik

IEEE Transactions on Human-Machine Systems
Year: 2022 | Volume: 52, Issue: 3 | Journal Article |
Cited by: Papers (11)
Human interaction recognition (HIR) is challenging due to multiple humans’ involvement and their mutual interaction in a single frame, generated from their movements. Mainstream literature is based on three-dimensional (3-D) convolutional neural networks (CNNs), processing only visual frames, where human joints data play a vital role in accurate interaction recognition. Therefore, this article pro...Show More

A Multi-Stream Sequence Learning Framework for Human Interaction Recognition

Umair Haroon;Amin Ullah;Tanveer Hussain;Waseem Ullah;Muhammad Sajjad;Khan Muhammad;Mi Young Lee;Sung Wook Baik

Year: 2022 | Volume: 52, Issue: 3 | Journal Article |

A Review on Traditional Machine Learning and Deep Learning Models for WBCs Classification in Blood Smear Images

Siraj Khan;Muhammad Sajjad;Tanveer Hussain;Amin Ullah;Ali Shariq Imran

IEEE Access
Year: 2021 | Volume: 9 | Journal Article |
Cited by: Papers (69)
In computer vision, traditional machine learning (TML) and deep learning (DL) methods have significantly contributed to the advancements of medical image analysis (MIA) by enhancing prediction accuracy, leading to appropriate planning and diagnosis. These methods substantially improved the diagnoses of automatic brain tumor and leukemia/blood cancer detection and can assist the hematologist and do...Show More

A Review on Traditional Machine Learning and Deep Learning Models for WBCs Classification in Blood Smear Images

Siraj Khan;Muhammad Sajjad;Tanveer Hussain;Amin Ullah;Ali Shariq Imran

Year: 2021 | Volume: 9 | Journal Article |

Batteries State of Health Estimation via Efficient Neural Networks With Multiple Channel Charging Profiles

Noman Khan;Fath U Min Ullah;Afnan;Amin Ullah;Mi Young Lee;Sung Wook Baik

IEEE Access
Year: 2021 | Volume: 9 | Journal Article |
Cited by: Papers (60)
The prognostics and health management (PHM) plays the main role to handle the risk of failure before its occurrence. Next, it has a broad spectrum of applications including utility networks, energy storage systems (ESS), etc. However, an accurate capacity estimation of batteries in ESS is mandatory for their safe operations and decision making policy. ESS comprises of different storage mechanisms ...Show More

Batteries State of Health Estimation via Efficient Neural Networks With Multiple Channel Charging Profiles

Noman Khan;Fath U Min Ullah;Afnan;Amin Ullah;Mi Young Lee;Sung Wook Baik

Year: 2021 | Volume: 9 | Journal Article |

Deep Learning for Safe Autonomous Driving: Current Challenges and Future Directions

Khan Muhammad;Amin Ullah;Jaime Lloret;Javier Del Ser;Victor Hugo C. de Albuquerque

IEEE Transactions on Intelligent Transportation Systems
Year: 2021 | Volume: 22, Issue: 7 | Journal Article |
Cited by: Papers (281)
Advances in information and signal processing technologies have a significant impact on autonomous driving (AD), improving driving safety while minimizing the efforts of human drivers with the help of advanced artificial intelligence (AI) techniques. Recently, deep learning (DL) approaches have solved several real-world problems of complex nature. However, their strengths in terms of control proce...Show More

Deep Learning for Safe Autonomous Driving: Current Challenges and Future Directions

Khan Muhammad;Amin Ullah;Jaime Lloret;Javier Del Ser;Victor Hugo C. de Albuquerque

Year: 2021 | Volume: 22, Issue: 7 | Journal Article |

Multiview Summarization and Activity Recognition Meet Edge Computing in IoT Environments

Tanveer Hussain;Khan Muhammad;Amin Ullah;Javier Del Ser;Amir H. Gandomi;Muhammad Sajjad;Sung Wook Baik;Victor Hugo C. de Albuquerque

IEEE Internet of Things Journal
Year: 2021 | Volume: 8, Issue: 12 | Journal Article |
Cited by: Papers (30)
Multiview video summarization (MVS) has not received much attention from the research community due to inter-view correlations and views' overlapping, etc. The majority of previous MVS works are offline, relying on only summary, and require additional communication bandwidth and transmission time, with no focus on foggy environments. We propose an edge intelligence-based MVS and activity recogniti...Show More

Multiview Summarization and Activity Recognition Meet Edge Computing in IoT Environments

Tanveer Hussain;Khan Muhammad;Amin Ullah;Javier Del Ser;Amir H. Gandomi;Muhammad Sajjad;Sung Wook Baik;Victor Hugo C. de Albuquerque

Year: 2021 | Volume: 8, Issue: 12 | Journal Article |

Event-Oriented 3D Convolutional Features Selection and Hash Codes Generation Using PCA for Video Retrieval

Amin Ullah;Khan Muhammad;Tanveer Hussain;Sung Wook Baik;Victor Hugo C. De Albuquerque

IEEE Access
Year: 2020 | Volume: 8 | Journal Article |
Cited by: Papers (14)
The extensive video surveillance networks gather an enormous amount of data exponentially on a daily basis and its management is a challenging task, requiring efficient and effective techniques for searching, indexing, and retrieval. The employed mainstream techniques are focusing on general category videos, where the important events in surveillance require fine-grained events retrieval. In this ...Show More

Event-Oriented 3D Convolutional Features Selection and Hash Codes Generation Using PCA for Video Retrieval

Amin Ullah;Khan Muhammad;Tanveer Hussain;Sung Wook Baik;Victor Hugo C. De Albuquerque

Year: 2020 | Volume: 8 | Journal Article |

One-Shot Learning for Surveillance Anomaly Recognition using Siamese 3D CNN

Amin Ullah;Khan Muhammad;Killichbek Haydarov;Ijaz Ul Haq;Miyoung Lee;Sung Wook Baik

2020 International Joint Conference on Neural Networks (IJCNN)
Year: 2020 | Conference Paper |
Cited by: Papers (21)
One-shot image recognition has been explored for many applications in computer vision community. However, its applications in video analytics is not deeply investigated yet. For instance, surveillance anomaly recognition is an open challenging problem and one of its hurdles is the lack of accurate temporally annotated data. This paper addresses the lack of data issue using one-shot learning strate...Show More

One-Shot Learning for Surveillance Anomaly Recognition using Siamese 3D CNN

Amin Ullah;Khan Muhammad;Killichbek Haydarov;Ijaz Ul Haq;Miyoung Lee;Sung Wook Baik

Year: 2020 | Conference Paper |

A Novel CNN-GRU-Based Hybrid Approach for Short-Term Residential Load Forecasting

Muhammad Sajjad;Zulfiqar Ahmad Khan;Amin Ullah;Tanveer Hussain;Waseem Ullah;Mi Young Lee;Sung Wook Baik

IEEE Access
Year: 2020 | Volume: 8 | Journal Article |
Cited by: Papers (274)
Electric energy forecasting domain attracts researchers due to its key role in saving energy resources, where mainstream existing models are based on Gradient Boosting Regression (GBR), Artificial Neural Networks (ANNs), Extreme Learning Machine (ELM) and Support Vector Machine (SVM). These models encounter high-level of non-linearity between input data and output predictions and limited adoptabil...Show More

A Novel CNN-GRU-Based Hybrid Approach for Short-Term Residential Load Forecasting

Muhammad Sajjad;Zulfiqar Ahmad Khan;Amin Ullah;Tanveer Hussain;Waseem Ullah;Mi Young Lee;Sung Wook Baik

Year: 2020 | Volume: 8 | Journal Article |

Short-Term Prediction of Residential Power Energy Consumption via CNN and Multi-Layer Bi-Directional LSTM Networks

Fath U Min Ullah;Amin Ullah;Ijaz Ul Haq;Seungmin Rho;Sung Wook Baik

IEEE Access
Year: 2020 | Volume: 8 | Journal Article |
Cited by: Papers (120)
Excessive Power Consumption (PC) and demand for power is increasing on a daily basis, due to advancements in technology, the rise in electricity-dependent machinery, and the growth of the human population. It has become necessary to predict PC in order to improve power management and co-operation between the energy used in a building and the power grid. State-of-the-art Energy Consumption Predicti...Show More

Short-Term Prediction of Residential Power Energy Consumption via CNN and Multi-Layer Bi-Directional LSTM Networks

Fath U Min Ullah;Amin Ullah;Ijaz Ul Haq;Seungmin Rho;Sung Wook Baik

Year: 2020 | Volume: 8 | Journal Article |

Cloud-Assisted Multiview Video Summarization Using CNN and Bidirectional LSTM

Tanveer Hussain;Khan Muhammad;Amin Ullah;Zehong Cao;Sung Wook Baik;Victor Hugo C. de Albuquerque

IEEE Transactions on Industrial Informatics
Year: 2020 | Volume: 16, Issue: 1 | Journal Article |
Cited by: Papers (100)
The massive amount of video data produced by surveillance networks in industries instigate various challenges in exploring these videos for many applications, such as video summarization (VS), analysis, indexing, and retrieval. The task of multiview video summarization (MVS) is very challenging due to the gigantic size of data, redundancy, overlapping in views, light variations, and interview corr...Show More

Cloud-Assisted Multiview Video Summarization Using CNN and Bidirectional LSTM

Tanveer Hussain;Khan Muhammad;Amin Ullah;Zehong Cao;Sung Wook Baik;Victor Hugo C. de Albuquerque

Year: 2020 | Volume: 16, Issue: 1 | Journal Article |

Efficient Image Recognition and Retrieval on IoT-Assisted Energy-Constrained Platforms From Big Data Repositories

Irfan Mehmood;Amin Ullah;Khan Muhammad;Der-Jiunn Deng;Weizhi Meng;Fadi Al-Turjman;Muhammad Sajjad;Victor Hugo C. de Albuquerque

IEEE Internet of Things Journal
Year: 2019 | Volume: 6, Issue: 6 | Journal Article |
Cited by: Papers (51)
The advanced computational capabilities of many resource constrained devices, such as smartphones have enabled various research areas including image retrieval from big data repositories for numerous Internet of Things (IoT) applications. The major challenges for image retrieval using smartphones in an IoT environment are the computational complexity and storage. To deal with big data in IoT envir...Show More

Efficient Image Recognition and Retrieval on IoT-Assisted Energy-Constrained Platforms From Big Data Repositories

Irfan Mehmood;Amin Ullah;Khan Muhammad;Der-Jiunn Deng;Weizhi Meng;Fadi Al-Turjman;Muhammad Sajjad;Victor Hugo C. de Albuquerque

Year: 2019 | Volume: 6, Issue: 6 | Journal Article |

DeepStar: Detecting Starring Characters in Movies

Ijaz Ul Haq;Khan Muhammad;Amin Ullah;Sung Wook Baik

IEEE Access
Year: 2019 | Volume: 7 | Journal Article |
Cited by: Papers (30)
Recent advances in the film industry have given rise to exponential growth in movie/drama production and adaptation of the Big Data concept. Automatic identification and classification of movie characters have received tremendous attention from researchers due to its applications in video semantic analysis, video summarization, and personalized video retrieval for which several methods have been r...Show More

DeepStar: Detecting Starring Characters in Movies

Ijaz Ul Haq;Khan Muhammad;Amin Ullah;Sung Wook Baik

Year: 2019 | Volume: 7 | Journal Article |

Activity Recognition Using Temporal Optical Flow Convolutional Features and Multilayer LSTM

Amin Ullah;Khan Muhammad;Javier Del Ser;Sung Wook Baik;Victor Hugo C. de Albuquerque

IEEE Transactions on Industrial Electronics
Year: 2019 | Volume: 66, Issue: 12 | Journal Article |
Cited by: Papers (134)
Nowadays digital surveillance systems are universally installed for continuously collecting enormous amounts of data, thereby requiring human monitoring for the identification of different activities and events. Smarter surveillance is the need of this era through which normal and abnormal activities can be automatically identified using artificial intelligence and computer vision technology. In t...Show More

Activity Recognition Using Temporal Optical Flow Convolutional Features and Multilayer LSTM

Amin Ullah;Khan Muhammad;Javier Del Ser;Sung Wook Baik;Victor Hugo C. de Albuquerque

Year: 2019 | Volume: 66, Issue: 12 | Journal Article |

Action Recognition in Video Sequences using Deep Bi-Directional LSTM With CNN Features

Amin Ullah;Jamil Ahmad;Khan Muhammad;Muhammad Sajjad;Sung Wook Baik

IEEE Access
Year: 2018 | Volume: 6 | Journal Article |
Recurrent neural network (RNN) and long short-term memory (LSTM) have achieved great success in processing sequential multimedia data and yielded the state-of-the-art results in speech recognition, digital signal processing, video processing, and text data analysis. In this paper, we propose a novel action recognition method by processing the video data using convolutional neural network (CNN) and...Show More

Action Recognition in Video Sequences using Deep Bi-Directional LSTM With CNN Features

Amin Ullah;Jamil Ahmad;Khan Muhammad;Muhammad Sajjad;Sung Wook Baik

Year: 2018 | Volume: 6 | Journal Article |

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