ENHANCING FRAGMENT-BASED VIDEO RETRIEVAL THROUGH THE INTEGRATION OF FEEDFORWARD NEURAL NETWORKS
DOI:
https://doi.org/10.30890/2709-2313.2024-27-00-004Keywords:
Video Search, Data Processing, Feature Extraction, Feedforward Neural NetworksAbstract
This paper delves into the evolving landscape of video search technology, tackling the intricate challenges posed by the exponential increase in video data. It highlights the critical need for advanced analytical tools to efficiently manage and retrieve vMetrics
References
BEI-JI ZOU et al. Enhanced Hexagonal-Based Search Using Direction-Oriented Inner Search for Motion Estimation. IEEE Transactions on Circuits and Systems for Video Technology [on-line]. Institute of Electrical and Electronics Engineers (IEEE), January 2010, Vol. 20, nr. 1, p. 156–160. DOI 10.1109/tcsvt.2009.2031461
SOCIAL MEDIA MARKETING, THE EFFECT OF THE SOCIAL MEDIA MARKETING ON BRANDS: A STUDY BASED ON GRATIS COSMATIC STORE IN ISTANBUL. Humanitarian and Natural Sciences Journal [on-line]. Brabdo for Educational Services, January 2024, Vol. 5, nr. 1.
DOI 10.53796/hnsj51/31.
SHAFIE, Hidayu, ABD MAJID, Faizah and ISMAIL, Izaham Shah. Technological Pedagogical Content Knowledge (TPACK) in Teaching 21st Century Skills in the 21st Century Classroom. Asian Journal of University Education [on-line]. UiTM Press, Universiti Teknologi MARA, December 2019, Vol. 15, nr. 3, p. 24.
DOI 10.24191/ajue.v15i3.7818
MA, Mingyang et al. Similarity Based Block Sparse Subset Selection for Video Summarization. IEEE Transactions on Circuits and Systems for Video Technology [on-line]. Institute of Electrical and Electronics Engineers (IEEE), October 2021, Vol. 31, nr. 10, p. 3967–3980. DOI 10.1109/tcsvt.2020.3044600.
SARAGIH, M. Yoserizal and HARAHAP, Ali Imran. The Challenges of Print Media Journalism in the Digital Era. Budapest International Research and Critics Institute (BIRCI-Journal) : Humanities and Social Sciences [on-line]. Budapest International Research and Critics Institute, February 2020, Vol. 3, nr. 1, p. 540–548. DOI 10.33258/birci.v3i1.805.
RAJENDRAN, Priya and SHANMUGAM, T.N. A content-based video retrieval system: video retrieval with extensive features. International Journal of Multimedia Intelligence and Security [on-line]. Inderscience Publishers, 2011, Vol. 2, nr. 2, p. 146. DOI 10.1504/ijmis.2011.041363.
COTSACES, C., NIKOLAIDIS, N. and PITAS, I. Video shot detection and condensed representation. a review. IEEE Signal Processing Magazine [on-line]. Institute of Electrical and Electronics Engineers (IEEE), March 2006, Vol. 23, nr. 2, p. 28–37. DOI 10.1109/msp.2006.1621446.
MOHAMMAD, Duaa, ALJARRAH, Inad and JARRAH, Moath. Searching surveillance video contents using convolutional neural network. International Journal of Electrical and Computer Engineering (IJECE) [on-line]. Institute of Advanced Engineering and Science, April 2021, Vol. 11, nr. 2, p. 1656.
DOI 10.11591/ijece.v11i2.pp1656-1665.
AL-SHAKARCHY, Noor D. Drowsy Detection based on Spatiotemporal Feature Extraction of Video Using 3D-CNN. Journal of Advanced Research in Dynamical and Control Systems [on-line]. Institute of Advanced Scientific Research, October 2019, Vol. 11, nr. 10-SPECIAL ISSUE, p. 742–751.
DOI 10.5373/jardcs/v11sp10/201928650.
ZENG, Yijie et al. Clustering via Adaptive and Locality-constrained Graph Learning and Unsupervised ELM. Neurocomputing [on-line]. Elsevier BV, August 2020, Vol. 401, p. 224–235. DOI 10.1016/j.neucom.2020.03.045.
2008 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP). IEEE Signal Processing Letters [on-line]. Institute of Electrical and Electronics Engineers (IEEE), July 2007, Vol. 14, nr. 7, p. 506–506.
DOI 10.1109/lsp.2007.902139.
WANG, Wenshi. Video Indexing and Retrieval based on Key Frame Extraction. International Journal of Performability Engineering [on-line]. Totem Publisher, Inc., 2018. DOI 10.23940/ijpe.18.08.p19.18241832.
ZHONG, Qi et al. Key Frame Extraction Algorithm of Motion Video Based on Priori. IEEE Access [on-line]. Institute of Electrical and Electronics Engineers (IEEE), 2020, Vol. 8, p. 174424–174436. DOI 10.1109/access.2020.3025774.
SOLANKI, Akshay et al. VEDL: A Novel Video Event Searching Technique Using Deep Learning. Advances in Intelligent Systems and Computing [on-line]. Singapore : Springer Singapore, 2020, p. 905–914.
DOI 10.1007/978-981-15-0751-9_83.
LIU, Zheng et al. Key News Event Detection and Event Context Using Graphic Convolution, Clustering, and Summarizing Methods. Applied Sciences [on-line]. MDPI AG, April 2023, Vol. 13, nr. 9, p. 5510. DOI 10.3390/app13095510.
THAIPANICH, Tanaphol, WU, Ping-Hao and KUO, C.-C. Low complexity algorithm for robust video frame rate up-conversion (FRUC) technique. IEEE Transactions on Consumer Electronics [on-line]. Institute of Electrical and Electronics Engineers (IEEE), February 2009, Vol. 55, nr. 1, p. 220–228.
DOI 10.1109/tce.2009.4814438.
MADRIGAL, Francisco and LERASLE, Frederic. Robust head pose estimation based on key frames for human-machine interaction. EURASIP Journal on Image and Video Processing [on-line]. Springer Science and Business Media LLC, March 2020, Vol. 2020, nr. 1. DOI 10.1186/s13640-020-0492-x.
ZARGARI, Farzad, MEHRABI, Mahdi and GHANBARI, Mohammad. Compressed domain texture based visual information retrieval method for I-frame coded pictures. IEEE Transactions on Consumer Electronics [on-line]. Institute of Electrical and Electronics Engineers (IEEE), May 2010, Vol. 56, nr. 2, p. 728–736. DOI 10.1109/tce.2010.5505994.
LI, Dengshan et al. A Recognition Method for Rice Plant Diseases and Pests Video Detection Based on Deep Convolutional Neural Network. Sensors [on-line]. MDPI AG, January 2020, Vol. 20, nr. 3, p. 578. DOI 10.3390/s20030578.
TOPTAŞ, Buket and HANBAY, Davut. A new artificial bee colony algorithm-based color space for fire/flame detection. Soft Computing [on-line]. Springer Science and Business Media LLC, November 2019, Vol. 24, nr. 14, p. 10481–10492. DOI 10.1007/s00500-019-04557-4.
QIUMEI, Zheng, DAN, Tan and FENGHUA, Wang. Improved Convolutional Neural Network Based on Fast Exponentially Linear Unit Activation Function. IEEE Access [on-line]. Institute of Electrical and Electronics Engineers (IEEE), 2019, Vol. 7, p. 151359–151367. DOI 10.1109/access.2019.2948112.
ZHANG, Xinliang and ZHOU, Shibo. WOA-DBSCAN: Application of Whale Optimization Algorithm in DBSCAN Parameter Adaption. IEEE Access [on-line]. Institute of Electrical and Electronics Engineers (IEEE), 2023, Vol. 11, p. 91861–91878. DOI 10.1109/access.2023.3307412.
ANDRE, Fabien, KERMARREC, Anne-Marie and LE SCOUARNEC, Nicolas. Quicker ADC : Unlocking the Hidden Potential of Product Quantization With SIMD. IEEE Transactions on Pattern Analysis and Machine Intelligence [on-line]. Institute of Electrical and Electronics Engineers (IEEE), May 2021, Vol. 43, nr. 5, p. 1666–1677. DOI 10.1109/tpami.2019.2952606.
KWON, Taehoon. Average Data Rate Analysis for Hierachical Cell Structure under Nakagami-m Fading Channel with a Two-layer Feed-Forward Neural Network. 2019 International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) [on-line]. IEEE, October 2019. DOI 10.1109/wimob.2019.8923280.
MEDUS, Leandro D. et al. A Novel Systolic Parallel Hardware Architecture for the FPGA Acceleration of Feedforward Neural Networks. IEEE Access [on-line]. Institute of Electrical and Electronics Engineers (IEEE), 2019, Vol. 7, p. 76084–76103. DOI 10.1109/access.2019.2920885.
LUO, Xiaoxia, YE, Ou and ZHOU, Beibei. An Modified Video Stream Classification Method Which Fuses Three-Dimensional Convolutional Neural Network. 2019 International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI) [on-line]. IEEE, November 2019.
DOI 10.1109/mlbdbi48998.2019.00026.
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