Now showing items 21-40 of 57

    • A regression-based framework for estimating the objective quality of HEVC coding units and video frames 

      Shanableh, Tamer (Elsevier, 2015-05)
      A no-reference objective quality estimation framework is proposed. The framework is suitable for any block-based video codec. In the proposed solution, features are extracted from coding units and summarized to form features ...
    • Saliency detection in MPEG and HEVC video using intra-frame and inter-frame distances 

      Shanableh, Tamer (Springer, 2016-04)
      This paper proposes a video saliency detection model for MPEG and HEVC coded videos. The model extracts features from MPEG macro blocks and HEVC coding units. The feature variables are based on syntax elements and statistics ...
    • Android mobile app for real-time bilateral Arabic sign language translation using leap motion controller 

      Eqab, Abdulla; Shanableh, Tamer (IEEE, 2017)
      This paper introduces an android mobile App for real-time bilateral Arabic sign language translation. The system is designed to operate on isolated sign language words. The mobile App has four main components; sign language ...
    • Decision-level fusion for single-view gait recognition with various carrying and clothing conditions 

      Al-Tayyan, Amer; Assaleh, Khaled; Shanableh, Tamer (Elsevier, 2017)
      Gait Recognition is one of the latest and attractive biometric techniques, due to its potential in identification of individuals at a distance, unobtrusively and even using low resolution images. In this paper we focus on ...
    • Altering Split Decisions of Coding Units for Message Embedding in HEVC 

      Shanableh, Tamer (Springer, 2017-05)
      This paper proposes a novel message embedding solution based on modifying the split decisions of HEVC videos. The encoder starts by computing a mapping between the split decisions of a Coding Unit (CU) and its features ...
    • Novel Classification System for Classifying Cognitive Workload Levels under Vague Visual Stimulation 

      Mahmoud, Rwan Adil Osman; Shanableh, Tamer; Bodala, Indu P.; Thakor, Nitish V.; Al-Nashash, Hasan (IEEE, 2017-07)
      This paper presents a novel method for classifying four different levels of cognitive workload. The workload levels are generated using visual stimuli degradation. EEG signals recorded from 16 subjects were used for workload ...
    • Predicting split decisions of coding units in HEVC video compression using machine learning techniques 

      Hassan, Mahitab Alaaeldin; Shanableh, Tamer (Springer, 2018)
      In this work, we propose to reduce the complexity of HEVC video encoding by predicting the split decisions of coding units. We use a sequencedependent approach in which a number of frames belonging to the video being encoded ...
    • Multiple Proposals for Continuous Arabic Sign Language Recognition 

      Hassan, Mohamed; Assaleh, Khaled; Shanableh, Tamer (Springer, 2019)
      The deaf community relies on sign language as the primary means of communication. For the millions of people around the world who suffer from hearing loss, interaction with hearing people is quite difficult. The main ...
    • Motion-Based Gait Recognition for Recognizing People in Traditional Gulf Clothing 

      Towheed, Mohammad Asif; Kiyani, Wasif; Ummar, Mumtaz; Shanableh, Tamer; Dhou, Salam (IEEE, 2019)
      Gait recognition is gaining popularity as it can recognize people in a non-intrusive and a non-contact manner. However, gait recognition is known for its susceptibility to clothing conditions. In this paper, we propose a ...
    • IoT-solar energy powered smart farm irrigation system 

      Al-Ali, A. R.; Al Nabulsi, Ahmad; Mukhopadhyay, Shayok; Awal, Mohammad Shihab; Fernandes, Sheehan; Ailabouni, Khalil Gihad (KeAi, 2019)
      As the Internet of things (IoT) technology is evolving, distributed solar energy resources can be operated, monitored, and controlled remotely. The design of an IoT based solar energy system for smart irrigation is essential ...
    • Using Linear Regression and Back Propagation Neural Networks to Predict Performance of Soiled PV Modules 

      Shapsough, Salsabeel Yousef; Dhaouadi, Rached; Zualkernan, Imran (Elsevier, 2019)
      This paper presents a study on neural network-based modeling techniques and sensor data to estimate the power output of photovoltaic systems under soiling conditions. Predicting maximum power output under soiling conditions ...
    • Internet of things based multi-sensor patient fall detection system 

      Khan, Sarah; Qamar, Ramsha; Zaheen, Rahma; Al-Ali, Abdul-Rahman; Al Nabulsi, Ahmad; Al-Nashash, Hasan (National Center for Biotechnology Information, 2019)
      Accidental falls of patients cannot be completely prevented. However, timely fall detection can help prevent further complications such as blood loss and unconsciousness. In this study, the authors present a cost-effective ...
    • IoT Based Smart City Bus Stops 

      Kamal, Miraal; Atif, Manal; Mujahid, Hafsa; Shanableh, Tamer; Al-Ali, Abdul-Rahman (MDPI, 2019)
      The advent of smart sensors, single system-on-chip computing devices, Internet of Things (IoT), and cloud computing is facilitating the design and development of smart devices and services. These include smart meters, smart ...
    • Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units 

      Shanableh, Tamer (Institution of Engineering and Technology, 2019-07)
      This paper proposes a data embedding solution in HEVC videos by modifying the partitioning of Coding Units (CUs). The partitions of a CU are first represented as a sequence of binary flags. The flags pertaining to 16x16 ...
    • Predicting Split Decisions in MPEG-2 to HEVC Video Transcoding 

      Shanableh, Tamer; Hassan, Mahitab Alaaeldin (Springer, 2020)
      This paper proposes learning-based approaches for transcoding MPEG-2 video into HEVC. In the training mode of the transcoder, mappings between extracted features and split decisions are calculated. While in the transcoding ...
    • Recursive Quad-Tree Block Partitioning for Data Embedding in Images 

      Shanableh, Tamer (Springer, 2020)
      In this paper, we propose to embed messages in raw images using a recursive block partitioning technique adopted from HEVC video coding technology. This work introduces a quad-tree partitioning solution in which square ...
    • Digital Twin Conceptual Model within the Context of Internet of Things 

      Al-Ali, A. R.; Gupta, Ragini; Batool, Tasneem Zaman; Landolsi, Taha; Aloul, Fadi; Al Nabulsi, Ahmad (MDPI, 2020)
      As the Internet of Things (IoT) is gaining ground and becoming increasingly popular in smart city applications such as smart energy, smart buildings, smart factories, smart transportation, smart farming, and smart healthcare, ...
    • Big Data Energy Management, Analytics and Visualization for Residential Areas 

      Gupta, Ragini; Al-Ali, A. R.; Zualkernan, Imran; Das, Sajal K. (IEEE, 2020)
      With the rapid development of IoT based home appliances, it has become a possibility that home owners share with Utilities in the management of home appliances energy consumption. Thus, the proposed work empowers home ...
    • Bioluminescence Imaging Applications in Cancer: A Comprehensive Review 

      AlSawaftah, Nour Majdi; Farooq, Afifa; Dhou, Salam; Majdalawieh, Amin (IEEE, 2020)
      Bioluminescence imaging (BLI), an optical preclinical imaging modality, is an invaluable imaging modality due to its low-cost, high throughput, fast acquisition times, and functional imaging capabilities. BLI is being ...
    • A New Data-Based Dust Estimation Unit for PV Panels 

      Shaaban, Mostafa; AlArif, Amal AbdulAziz; Mokhtar, Mohamed; Tariq, Usman; Osman, Ahmed; Al-Ali, A. R. (MDPI, 2020)
      Solar photovoltaic (PV) is playing a major role in the United Arab Emirates (UAE) smart grid infrastructure. However, one of the challenges facing PV-based energy systems is the dust accumulation on solar panels. Dust ...