Search Results - (( frames extraction learning algorithm ) OR ( java application stemming algorithm ))

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  1. 1

    AR oriented pose matching mechanism from motion capture data by Iqbal J., Sidhu M.S., Ariff M.B.M.

    Published 2023
    “…In order to extract the exact matched pose, the frame sequence is divided into pose feature frame and skeletal data frame by the use of pose matching dance training movement recognition algorithm (PMDTMR). …”
    Article
  2. 2

    Particle swarm optimization with deep learning for human action recognition by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

    Published 2021
    “…The regions extracted by these algorithms are larger than the region of interest and stretches towards the direction of movement. …”
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    Article
  3. 3

    A Reinforcement Learning Based Adaptive ROI Generation for Video Object Segmentation by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

    Published 2021
    “…Our framework is trained using pairs (or groups) of video frames, which adds to the training content, thus increasing the learning capacity. …”
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    Article
  4. 4

    Deep learning-based water segmentation for autonomous surface vessel by Mohd Adam, Muhammad Ammar, Ibrahim, Ahmad Imran, Zainal Abidin, Zulkifli, Mohd Zaki, Hasan Firdaus

    Published 2020
    “…Classical computer vision algorithms for detection holds limitation in robustness and scalability. …”
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    Proceeding Paper
  5. 5

    An integrated deep learning deepfakes detection method (IDL-DDM) by Yassin, Warusia, Johan, Azwan, Abas, Zuraida Abal, Baharon, Mohd Rizuan, Bejuri, Wan, Ismail, Anuar

    Published 2024
    “…In addition, the Long Short-Term Memory (LSTM) approach is applied consecutively after CNN in order to grant sequential processing of data and overcome learning dependencies. Using this learning algorithm, several facial region characteristics such as eyes, nose, and mouth are extracted and further transformed into numerical form with the intention to identify video frames more precisely. …”
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    Conference or Workshop Item
  6. 6

    Adaptive Non-Stationary Cardiac Signals Identification using an Augmented MLP Network by Asirvadam , Vijanth Sagayan, McLoone, Sean

    Published 2007
    “…It will be also an ideal case when dealing with ECG signals where the pattern of signals varies as it depends on the condition of patience at very short frame of time.In this paper the recursive learning algorithms is being tested on an Augmented a Multilayer- Perceptron (MLP) or also known as Direct-Link MLP (DMLP) networks. …”
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    Conference or Workshop Item
  7. 7

    Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm by Ismail, Asmida, Ahmad, Siti Anom, Che Soh, Azura, Hassan, Mohd Khair, Harith, Hazreen Haizi

    Published 2020
    “…This paper presented an analysis performance of deep learning object detector by combining a deep learning Convolutional Neural Network (CNN) for object classification and applies classic object detection algorithms to devise our own deep learning object detector. …”
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    Article
  8. 8

    Autism spectrum self-stimulatory behaviours classification using explainable temporal coherency deep networks and SVM classifier / Liang Shuaibing by Liang , Shuaibing

    Published 2022
    “…In recent years, the advancement of deep learning algorithms and hardware enabled the use of artificial intelligence technology to automatically capture self-stimulatory behaviours. …”
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    Thesis
  9. 9

    CNN architectures for road surface wetness classification from acoustic signals by Bahrami, Siavash, Doraisamy, Shyamala, Azman, Azreen, Nasharuddin, Nurul Amelina, Yue, Shigang

    “…Recorded acoustic signals were segmented into equal frames and thirteen MFCCs were extracted for each frame to train the CNNs. …”
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    Article
  10. 10

    Enhanced emotion recognition in videos: a convolutional neural network strategy for human facial expression detection and classification by Ashraf, Arselan, Gunawan, Teddy Surya, Arifin, Fatchul, Kartiwi, Mira, Sophian, Ali, Habaebi, Mohamed Hadi

    Published 2023
    “…We employ the Amsterdam Dynamic Facial Expression Set – Bath Intensity Variations (ADFES-BIV) video dataset, extracting image frames from the video samples. Image processing techniques such as histogram equalization, color conversion, cropping, and resizing are applied to the frames before labeling. …”
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    Article
  11. 11

    Deep learning enabled fall detection exploiting gait analysis by Anwary, Arif Reza, Rahman, Md Arafatur, Abu Jafar, Md Muzahid, Ul Ashraf, Akanda Wahid, Patwary, Mohammad Nuruzzaman, Hussain, Amir

    Published 2022
    “…Secondly, we discussed the proposed DLFD method which exploits fall and non-fall RGB video to extract gait features using MediaPipe framework, applies normalization algorithm and classifies using bi-directional Long Short-Term Memory (bi-LSTM) model. …”
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    Conference or Workshop Item
  12. 12

    A vision-based deep learning approach for non-contact vibration measurement using (2+1)D CNN and optical flow by Harold Harrison, Mazlina Mamat, Farah Wong, Hoe Tung Yew, Racheal Lim, Wan Mimi Diyana Wan Zaki

    Published 2025
    “…Techniques such as Region of Interest (ROI) cropping and multi-section frame extraction were implemented to reduce computational complexity while further enhancing accuracy. …”
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    Article