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Journal articles on the topic 'Frame network'

Author: Grafiati

Published: 3 June 2025

Last updated: 1 August 2025

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1

Yan, Bo, Chuming Lin, and Weimin Tan. "Frame and Feature-Context Video Super-Resolution." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 5597–604. http://dx.doi.org/10.1609/aaai.v33i01.33015597.

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For video super-resolution, current state-of-the-art approaches either process multiple low-resolution (LR) frames to produce each output high-resolution (HR) frame separately in a sliding window fashion or recurrently exploit the previously estimated HR frames to super-resolve the following frame. The main weaknesses of these approaches are: 1) separately generating each output frame may obtain high-quality HR estimates while resulting in unsatisfactory flickering artifacts, and 2) combining previously generated HR frames can produce temporally consistent results in the case of short informat

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Lu, Fan, Guang Chen, Sanqing Qu, Zhijun Li, Yinlong Liu, and Alois Knoll. "PointINet: Point Cloud Frame Interpolation Network." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 3 (2021): 2251–59. http://dx.doi.org/10.1609/aaai.v35i3.16324.

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LiDAR point cloud streams are usually sparse in time dimension, which is limited by hardware performance. Generally, the frame rates of mechanical LiDAR sensors are 10 to 20 Hz, which is much lower than other commonly used sensors like cameras. To overcome the temporal limitations of LiDAR sensors, a novel task named Point Cloud Frame Interpolation is studied in this paper. Given two consecutive point cloud frames, Point Cloud Frame Interpolation aims to generate intermediate frame(s) between them. To achieve that, we propose a novel framework, namely Point Cloud Frame Interpolation Network (P

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Ouyang, Ning, Zhishan Ou, and Leping Lin. "Video Super-Resolution Network with Gated High-Low Resolution Frames." Applied Sciences 13, no. 14 (2023): 8299. http://dx.doi.org/10.3390/app13148299.

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In scenes with large inter-frame motion variations, distant targets, and blurred targets, the lack of inter-frame alignment can greatly affect the effectiveness of subsequent video super-resolution reconstruction. How to perform inter-frame alignment in such scenes is the key to super-resolution reconstruction. In this paper, a new motion compensation method is proposed to design an alignment network based on gated high-low resolution frames. The core idea is to introduce a gating mechanism while using the information of high-low resolution neighboring frames to perform motion compensation ada

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Jadhav, Savita, and Sangeeta Jadhav. "VHFRP: Virtual Hexagonal Frame Routing Protocol for Wireless Sensor Network." International journal of Computer Networks & Communications 15, no. 2 (2023): 39–55. http://dx.doi.org/10.5121/ijcnc.2023.15203.

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As physical and digital worlds become increasingly intertwined, wireless sensor networks are becoming an indispensable technology. A mobile sink may be required for some applications in the sensor field, where incomplete and/or delayed data delivery can lead to inappropriate conclusions. Therefore, latency and packet delivery ratios must be of high quality. In most existing schemes, mobile sinks are used to extend network lifetimes. By partitioning the sensor field into k equal sized frames, the proposed scheme creates a virtual hexagonal structure. Each frame header (FH) is linked together th

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Li, Jiaao, Qunbo Lv, Wenjian Zhang, Yu Zhang, and Zheng Tan. "Burst-Enhanced Super-Resolution Network (BESR)." Sensors 24, no. 7 (2024): 2052. http://dx.doi.org/10.3390/s24072052.

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Multi-frame super-resolution (MFSR) leverages complementary information between image sequences of the same scene to increase the resolution of the reconstructed image. As a branch of MFSR, burst super-resolution aims to restore image details by leveraging the complementary information between noisy sequences. In this paper, we propose an efficient burst-enhanced super-resolution network (BESR). Specifically, we introduce Geformer, a gate-enhanced transformer, and construct an enhanced CNN-Transformer block (ECTB) by combining convolutions to enhance local perception. ECTB efficiently aggregat

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Nakayama, Yu, and Kaoru Sezaki. "Per-Flow Throughput Fairness in Ring Aggregation Network with Multiple Edge Routers." Big Data and Cognitive Computing 2, no. 3 (2018): 17. http://dx.doi.org/10.3390/bdcc2030017.

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Ring aggregation networks are often employed by network carriers because of their efficiency and high fault tolerance. A fairness scheme is required in ring aggregation to achieve per-flow throughput fairness and bufferbloat avoidance, because frames are forwarded along multiple ring nodes. N Rate N + 1 Color Marking (NRN + 1CM) was proposed to achieve fairness in ring aggregation networks consisting of Layer-2 Switches (SWs). With NRN + 1CM, frames are selectively discarded based on color and the frame-dropping threshold. To avoid the accumulation of a queuing delay, frames are discarded at u

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Volodymyr, Khandetskyi, and Karpenko Nadiia. "Analysis of the efficiency of block frame transmission in IEEE 802.11 computer networks." System technologies 1, no. 150 (2024): 158–65. http://dx.doi.org/10.34185/1562-9945-1-150-2024-16.

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In infrastructure schemes of WLANs wireless computer networks, which are based on the use of the DSF (distributed coordination function) function and the CSMA/CA mechanism, the station STA (STAtion) sends a frame if the transmission channel is released after waiting for the end of the DIFS (distributed interframe space) interval and operation of the slot selec-tion mechanism for transmission (backoff mechanism). In case of collisions or damage to the frame by interference, the AP cannot decode the frame and does not send it back to the ACS station. The sending station STA waits for the re-ceip

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Lan, Meng, Jing Zhang, Fengxiang He, and Lefei Zhang. "Siamese Network with Interactive Transformer for Video Object Segmentation." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 2 (2022): 1228–36. http://dx.doi.org/10.1609/aaai.v36i2.20009.

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Semi-supervised video object segmentation (VOS) refers to segmenting the target object in remaining frames given its annotation in the first frame, which has been actively studied in recent years. The key challenge lies in finding effective ways to exploit the spatio-temporal context of past frames to help learn discriminative target representation of current frame. In this paper, we propose a novel Siamese network with a specifically designed interactive transformer, called SITVOS, to enable effective context propagation from historical to current frames. Technically, we use the transformer e

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Kim, Jeongmin, and Yong Ju Jung. "Multi-Stage Network for Event-Based Video Deblurring with Residual Hint Attention." Sensors 23, no. 6 (2023): 2880. http://dx.doi.org/10.3390/s23062880.

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Video deblurring aims at removing the motion blur caused by the movement of objects or camera shake. Traditional video deblurring methods have mainly focused on frame-based deblurring, which takes only blurry frames as the input to produce sharp frames. However, frame-based deblurring has shown poor picture quality in challenging cases of video restoration where severely blurred frames are provided as the input. To overcome this issue, recent studies have begun to explore the event-based approach, which uses the event sequence captured by an event camera for motion deblurring. Event cameras ha

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Xing, Guansheng, and Ziming Zhu. "Lane and Road Marker Semantic Video Segmentation Using Mask Cropping and Optical Flow Estimation." Sensors 21, no. 21 (2021): 7156. http://dx.doi.org/10.3390/s21217156.

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Lane and road marker segmentation is crucial in autonomous driving, and many related methods have been proposed in this field. However, most of them are based on single-frame prediction, which causes unstable results between frames. Some semantic multi-frame segmentation methods produce error accumulation and are not fast enough. Therefore, we propose a deep learning algorithm that takes into account the continuity information of adjacent image frames, including image sequence processing and an end-to-end trainable multi-input single-output network to jointly process the segmentation of lanes

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Kollias, Andreas, Fani Kountouri, and Sofia Kalamanti. "Framing Migration Through the Crisis Era 2015–2022: A Content and Semantic Network Analysis of the Greek Press." Journalism and Media 6, no. 1 (2025): 4. https://doi.org/10.3390/journalmedia6010004.

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Since the 2015 refugee crisis, when over 850,000 refugees and migrants reached European shores, migration has sparked intense political and social debates that dominate Europe’s political and media agenda. As a key entry point for refugees and migrants, Greece plays a central role in this ongoing crisis. This study examines how migration has been framed in three major Greek news outlets from 2015 to 2022. This study is groundbreaking as it goes beyond analyzing how mainstream media portray migration, migrants, and refugees. It also examines how the media frame the rhetoric and actions of far-r

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Lin, Zhicheng, Rongpu Cui, Limiao Ning, and Jian Peng. "Temporal Features-Fused Vision Retentive Network for Echocardiography Image Segmentation." Sensors 25, no. 6 (2025): 1909. https://doi.org/10.3390/s25061909.

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Echocardiography is a widely used cardiac imaging modality in clinical practice. Physicians utilize echocardiography images to measure left ventricular volumes at end-diastole (ED) and end-systole (ES) frames, which are pivotal for calculating the ejection fraction and thus quantitatively assessing cardiac function. However, most existing approaches focus on features from ES frames and ED frames, neglecting the inter-frame correlations in unlabeled frames. Our model is based on an encoder–decoder architecture and consists of two modules: the Temporal Feature Fusion Module (TFFA) and the Vision

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Wang, Meiju, Guoqiang Zhong, Zhaoyang Deng, Kang Zhang, and Peng Jiang. "Recurrent Adversarial Video Prediction Network." Journal of Physics: Conference Series 2278, no. 1 (2022): 012016. http://dx.doi.org/10.1088/1742-6596/2278/1/012016.

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Abstract Mining the intrinsic information of sequential data to predict the future data has a promising research prospect. Considering the temporal features of sequential data, existing approaches generally adopt recurrent neural network and its variants for the prediction. However, for sequences with complex structure, such as video frame sequence, these approaches cannot guarantee to obtain promising prediction results. In this paper, to address the above issue, we propose a novel architecture, called recurrent adversarial video prediction network (RAVPN), which can not only extract the temp

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Chen, Bo, Fangzhou Meng, Hongying Tang, and Guanjun Tong. "Two-Level Attention Module Based on Spurious-3D Residual Networks for Human Action Recognition." Sensors 23, no. 3 (2023): 1707. http://dx.doi.org/10.3390/s23031707.

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In recent years, deep learning techniques have excelled in video action recognition. However, currently commonly used video action recognition models minimize the importance of different video frames and spatial regions within some specific frames when performing action recognition, which makes it difficult for the models to adequately extract spatiotemporal features from the video data. In this paper, an action recognition method based on improved residual convolutional neural networks (CNNs) for video frames and spatial attention modules is proposed to address this problem. The network can g

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Kim, Tae Hyung, Cheol Woo Park, and Il Kyu Eom. "Frame Identification of Object-Based Video Tampering Using Symmetrically Overlapped Motion Residual." Symmetry 14, no. 2 (2022): 364. http://dx.doi.org/10.3390/sym14020364.

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Image and video manipulation has been actively used in recent years with the development of multimedia editing technologies. However, object-based video tampering, which adds or removes objects within a video frame, is posing challenges because it is difficult to verify the authenticity of videos. In this paper, we present a novel object-based frame identification network. The proposed method uses symmetrically overlapped motion residuals to enhance the discernment of video frames. Since the proposed motion residual features are generated on the basis of overlapped temporal windows, temporal v

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Osipov, Vassilii, and Viktor Nikiforov. "Recurrent neural networks with controlled elements in restoring frame flows." Information and Control Systems, no. 5 (October 16, 2019): 10–17. http://dx.doi.org/10.31799/1684-8853-2019-5-10-17.

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Introduction: Various interfering influences raise pressing problems of promptly restoring the flow of distorted frames,remembering about the background and dynamics of the event measurement laws. The traditional methods of recovering flows ofdistorted frames do not fully take into account the peculiarities of this process. Purpose: Exploring the possibilities of recurrent neuralnetworks with controlled elements for restoring frame flows. Results: It is proposed to evaluate the potential of a recurrent neuralnetwork with controlled elements by the number of successful options for restoring a d

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Farrell, Maureen. "Health care leadership in an age of change." Australian Health Review 26, no. 1 (2003): 153. http://dx.doi.org/10.1071/ah030153.

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This study examined the leadership practices of a sample of network and hospital administrators in metropolitan Victoria, Australia. It was undertaken in the mid-1990s when the State Liberal-National (Coalition) Government in Victoria established Melbourne's metropolitan health care networks. I argue that leadership,and the process of leading, contributes significantly to the success of the hospital in a time of turmoil and change.The sample was taken from the seven health care networks and consisted of 15 network and hospital administrators. Bolman and Deal's frames of leadership - structural

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Zhu, Guang, Yajuan Liu, and Jiyue Wang. "Multi-frame network feature fusion model and self-attention mechanism for vehicle lane line detection." Computer Science and Information Systems, no. 00 (2024): 54. http://dx.doi.org/10.2298/csis240314054z.

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The traditional lane detection networks mainly use independent single frame images to extract features first and then detect them, which cannot deal with the scene with complex background well. Therefore, this paper proposes a lane parallel detection network based on multi-frame network feature fusion model and self-attention mechanism according to the scene characteristics that vehicles can obtain continuous images during normal driving. Firstly, a parallel feature extraction structure is designed. On the one hand, a single frame network with high precision is used to extract the features of

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Conway-Silva, Bethany Anne. "Exploring the Networks of News Production: Frame Building and Source Use During the 2014 U.S. Midterm Elections." Journalism & Mass Communication Quarterly 96, no. 2 (2018): 537–57. http://dx.doi.org/10.1177/1077699018803083.

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This study of the 2014 U.S. midterm congressional elections examined whether connections across sources within newspaper coverage predicted framing outcomes. Conceptualized as an aspect of frame building, symbolic source networks within articles were examined using social network analysis and multilevel modeling. Results suggest network density within a given article predicted the likelihood that a source was linked to the strategic game frame and issue frame in election coverage. By nesting sources within networks, this study extends our understanding of frame building and collective sense-ma

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Berezkin, A. A., R. M. Vivchar, A. A. Chenskiy, and R. V. Kirichek. "Research of Video Stream Frame Delay in UAV FPV-Control Information Exchange Channel in Hybrid Communication Network Terrestrial Segment." Proceedings of Telecommunication Universities 11, no. 1 (2025): 7–17. https://doi.org/10.31854/1813-324x-2025-11-1-7-17.

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This research considers the dependence of the delay and loss of video stream frames compressed by neural network codec developed on the basis of neural network variation auto-encoder on the size of transmitted frames in the realization of information exchange channels between unmanned aviation system and external pilot station in the ground segment of hybrid orbital-terrestrial communication network taking into account the distance between them when using 3G and LTE data transmission technologies are used. The Relevance of the research is conditioned by the necessity to achieve a given level o

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Evans, Robert. "CPED Framework as a Network-Level Signature Pedagogy." Impacting Education: Journal on Transforming Professional Practice 8, no. 3 (2023): 44–49. http://dx.doi.org/10.5195/ie.2023.349.

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The CPED Framework (CPED, 2022) envisions the EdD as a professionally-oriented alternative to the PhD. Within the framework, two professional aims are proposed: stewardship and scholarly practice. In this essay, I distinguish between the two terms, exploring how Erving Goffman’s (1986) concept of frame analysis can be a useful approach to stewardship. I contrast Goffman’s (1986) approach with that of frame alignment (Snow et al., 1986), noting that frames are useful for clarifying the improvement efforts of scholarly practice while also putting those who use them at risk of encapsulation. I ex

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Novoa Jaso, María Fernanda, and Ruth Breeze. "Framing the Russia-Ukraine conflict in Chinese Global Television Network English." Tripodos, no. 56 (October 25, 2024): 03. https://doi.org/10.51698/tripodos.2024.56.03.

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This article examines the coverage of the conflict in Ukraine on the CGTN English website during the first three months. Through a quantitative content analysis of 1,799 news items, this research identifies the predominant frames, social actors, and sources of information employed in the media coverage. The results reveal that the “diplomatic frame” predominates, followed by the “war frame”. The “economic frame” gains more prominence over time, compared to the “human interest frame”. Over these months, CGTN moves from an impartial descriptive approach to one that attributes responsibility vari

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Chandrakala, Chandrakala, and Mungamuri Sasikala. "An efficient novel dual deep network architecture for video forgery detection." International Journal of Reconfigurable and Embedded Systems (IJRES) 13, no. 2 (2024): 458. http://dx.doi.org/10.11591/ijres.v13.i2.pp458-471.

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The technique of video copy-move forgery (CMF) is commonly employed in various industries; digital videography is regularly used as the foundation for vital graphic evidence that may be modified using the aforementioned method. Recently in the past few decades, forgery in digital images is detected via machine intellect. The second issue includes continuous allocation of parallel frames having relevant backgrounds erroneously results in false implications, detected as CMF regions third include as the CMF is divided into inter-frame or intra-frame forgeries to detect video copy is not possible

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Devyatiyarov, Dmitriy. "Network Frame Hostile Encounter in Russian Internet Comments." Virtual Communication and Social Networks 2022, no. 4 (2022): 191–95. http://dx.doi.org/10.21603/2782-4799-2022-1-4-191-195.

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The article deals with the structure and content of the network frame hostile encounter in the Internet comments to a Russian video that featured the special military operation in Ukraine. The current political situation has turned many Internet resources into a platform of information-psychological warfare. Network discourse is anonymous and moderated by the resource owners. For instance, YouTube videos and comments can have a manipulative effect on Internet users, who develop certain mental frames as a result of interaction of mental and language structures. Charles Fillmore defined frames a

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Zhang, Haoxian, Ronggang Wang, and Yang Zhao. "Multi-Frame Pyramid Refinement Network for Video Frame Interpolation." IEEE Access 7 (2019): 130610–21. http://dx.doi.org/10.1109/access.2019.2940510.

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Prokhorova, Olga Nikolaevna, and Olga Nikolaevna Polshchykova. "A terminological frame-network model of the conceptual and semantic organization of notions of computational linguistics." Philology. Issues of Theory and Practice 17, no. 2 (2024): 265–72. http://dx.doi.org/10.30853/phil20240038.

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The research object is the conceptual and semantic organization of the terminological apparatus, the research subject is the logical and conceptual structure of notions denoted by terms of computational linguistics. The study aims to identify the features of the systemic organization of notions of computational linguistics based on the use of a terminological frame-network model. The paper briefly analyzes the use of the frame approach to modeling the structure of terminological systems by linguists. A terminological frame-network model of the subject area “Computational linguistics” is propos

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Kresnadi Putra, I. Putu Eka Giri Setya, Gede Sukadarmika, and Ni Made A. E. D. Wirastuti. "KUALITAS LAYANAN JUMBO FRAME PADA PROSES TRANSFER DATA FAKULTAS TEKNIK KAMPUS SUDIRMAN UNIVERSITAS UDAYANA." Jurnal SPEKTRUM 6, no. 3 (2019): 52. http://dx.doi.org/10.24843/spektrum.2019.v06.i03.p07.

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The development of network technology is increasingly growing. The high amount of digital data passed on computer networks is currently influenced by the increasing use and need of the era of digitalization. Therefore it is required reliable network conditions and can provide time efficiency. This final project analyzed the effect of jumbo frame service quality on data transfer process. The experiment conducted int two types frame network that is normal frame and jumbo frame network. It is found that the best average of frame size is 5000 bytes. In term of QoS parameters obtained that for pack

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Xin, Jingwei, Nannan Wang, Jie Li, Xinbo Gao, and Zhifeng Li. "Video Face Super-Resolution with Motion-Adaptive Feedback Cell." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (2020): 12468–75. http://dx.doi.org/10.1609/aaai.v34i07.6934.

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Video super-resolution (VSR) methods have recently achieved a remarkable success due to the development of deep convolutional neural networks (CNN). Current state-of-the-art CNN methods usually treat the VSR problem as a large number of separate multi-frame super-resolution tasks, at which a batch of low resolution (LR) frames is utilized to generate a single high resolution (HR) frame, and running a slide window to select LR frames over the entire video would obtain a series of HR frames. However, duo to the complex temporal dependency between frames, with the number of LR input frames increa

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Latha, S., and Sinthu Janita Prakash. "IDSFS: A Signature Based Intrusion Detection System with High Pertinent Feature Selection Method." Asian Journal of Computer Science and Technology 8, no. 2 (2019): 25–31. http://dx.doi.org/10.51983/ajcst-2019.8.2.2145.

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Securing a network from the attackers is a challenging task at present as many users involve in variety of computer networks. To protect any individual host in a network or the entire network, some security system must be implemented. In this case, the Intrusion Detection System (IDS) is essential to protect the network from the intruders. The IDS have to deal with a lot of network packets with different characteristics. A signature-based IDS is a potential tool to understand former attacks and to define suitable method to conquest it in variety of applications. This research article elucidate

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Latha, S., and Sinthu Janita Prakash. "A Signature Based Intrusion Detection System with HPFSM and Fuzzy Based Classification Method (IDSFSC)." Asian Journal of Engineering and Applied Technology 8, no. 2 (2019): 23–29. http://dx.doi.org/10.51983/ajeat-2019.8.2.1144.

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Securing a network from the attackers is a challenging task at present as many users involve in variety of computer networks. To protect any individual host in a network or the entire network, some security system must be implemented. In this case, the Intrusion Detection System (IDS) is essential to protect the network from the intruders. The IDS has to deal with a lot of network packets with different characteristics. A signature-based IDS is a potential tool to understand former attacks and to define suitable method to conquest it in variety of applications. This research article elucidates

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Abdelkarim, M., M. K. Abbas, Alaa Osama, et al. "GG-Net: Gaze Guided Network for Self-driving Cars." Electronic Imaging 2021, no. 17 (2021): 171–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.17.avm-171.

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Imitation learning is used massively in autonomous driving for training networks to predict steering commands from frames using annotated data collected by an expert driver. Believing that the frames taken from a front-facing camera are completely mimicking the driver’s eyes raises the question of how eyes and the complex human vision system attention mechanisms perceive the scene. This paper proposes the idea of incorporating eye gaze information with the frames into an end-to-end deep neural network in the lane-following task. The proposed novel architecture, GG-Net, is composed of a spatial

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Butt, Rizwan Aslam, Sevia Mahdaliza Idrus, Raja Zahilah Radzi, and Kashif Naseer Qureshi. "Energy Efficient Frame Structure for Gigabit Passive Optical Networks." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 6 (2016): 2971. http://dx.doi.org/10.11591/ijece.v6i6.11109.

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<p>Increasing power consumption in information and communication access networks is one of the major cause of greenhouse gas emissions. These emissions are harmful to life on earth. Passive Optical Networks (PONs) are energy efficient but the broadcast nature of downstream traffic may cause of huge unnecessary processing of frames by the optical network units and result in significant energy wastage. Bi-PON technique tried to solve this problem by changing the XGPON / GPON frame structure to an interleaved pattern but also required additional hardware changings at the optical network uni

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Butt, Rizwan Aslam, Sevia Mahdaliza Idrus, Raja Zahilah Radzi, and Kashif Naseer Qureshi. "Energy Efficient Frame Structure for Gigabit Passive Optical Networks." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 6 (2016): 2971. http://dx.doi.org/10.11591/ijece.v6i6.pp2971-2978.

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<p>Increasing power consumption in information and communication access networks is one of the major cause of greenhouse gas emissions. These emissions are harmful to life on earth. Passive Optical Networks (PONs) are energy efficient but the broadcast nature of downstream traffic may cause of huge unnecessary processing of frames by the optical network units and result in significant energy wastage. Bi-PON technique tried to solve this problem by changing the XGPON / GPON frame structure to an interleaved pattern but also required additional hardware changings at the optical network uni

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Meon, Mohd Suhairil, Muhammad Azhan Anuar, Mohd Hanif Mohd Ramli, Wahyu Kuntjoro, and Zulkifli Muhammad. "Frame Optimization using Neural Network." International Journal on Advanced Science, Engineering and Information Technology 2, no. 1 (2012): 28. http://dx.doi.org/10.18517/ijaseit.2.1.148.

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Fan, Bing Hui, Peng Ji, and Kai Zhou. "The Implementation of Pipe Climbing Robot’s Real-Time Speech Control Based on the Generalized Regression Neural Network in Embedded System." Applied Mechanics and Materials 220-223 (November 2012): 1986–89. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.1986.

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This paper describes a speech pre-processing and feature extraction methods and described the principle of generalized regression neural network (GRNN). In order to use neural networks for speech recognition, this article uses the variable frame-shift average frame method to average the characteristic parameters of the collected voice frame, and the feasibility of the variable frame-shift average frame method in neural network input parameters normalization is verified by experiments. In this paper, according to this method, the speech recognition based on the generalized regression neural net

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Yao, Chuanhong, and Haitao Zhao. "Adaptive Frame Sampling and Feature Alignment for Multi-Frame Infrared Small Target Detection." Applied Sciences 14, no. 14 (2024): 6360. http://dx.doi.org/10.3390/app14146360.

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In recent years, infrared images have attracted widespread attention, due to their extensive application in low-visibility search and rescue, forest fire monitoring, ground target monitoring, and other fields. Infrared small target detection technology plays a vital role in these applications. Although there has been significant research over the years, accurately detecting infrared small targets in complex backgrounds remains a significant challenge. Multi-frame detection methods can significantly improve detection performance in these cases. However, current multi-frame methods face difficul

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Choi, Jinsoo, and Tae-Hyun Oh. "Joint Video Super-Resolution and Frame Interpolation via Permutation Invariance." Sensors 23, no. 5 (2023): 2529. http://dx.doi.org/10.3390/s23052529.

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We propose a joint super resolution (SR) and frame interpolation framework that can perform both spatial and temporal super resolution. We identify performance variation according to permutation of inputs in video super-resolution and video frame interpolation. We postulate that favorable features extracted from multiple frames should be consistent regardless of input order if the features are optimally complementary for respective frames. With this motivation, we propose a permutation invariant deep architecture that makes use of the multi-frame SR principles by virtue of our order (permutati

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Song, Qiang, and Hangfan Liu. "Deep Gradient Prior Regularized Robust Video Super-Resolution." Electronics 10, no. 14 (2021): 1641. http://dx.doi.org/10.3390/electronics10141641.

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This paper proposes a robust multi-frame video super-resolution (SR) scheme to obtain high SR performance under large upscaling factors. Although the reference low-resolution frames can provide complementary information for the high-resolution frame, an effective regularizer is required to rectify the unreliable information from the reference frames. As the high-frequency information is mostly contained in the image gradient field, we propose to learn the gradient-mapping function between the high-resolution (HR) and the low-resolution (LR) image to regularize the fusion of multiple frames. In

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Zhang, Haokai, Dongwei Ren, Zifei Yan, and Wangmeng Zuo. "Arbitrary Timestep Video Frame Interpolation with Time-Dependent Decoding." Mathematics 12, no. 2 (2024): 303. http://dx.doi.org/10.3390/math12020303.

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Given an observed low frame rate video, video frame interpolation (VFI) aims to generate a high frame rate video, which has smooth video frames with higher frames per second (FPS). Most existing VFI methods often focus on generating one frame at a specific timestep, e.g., 0.5, between every two frames, thus lacking the flexibility to increase the video’s FPS by an arbitrary scale, e.g., 3. To better address this issue, in this paper, we propose an arbitrary timestep video frame interpolation (ATVFI) network with time-dependent decoding. Generally, the proposed ATVFI is an encoder–decoder archi

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Zhu, Yanping, Jianbo Gong, and Xin Sun. "The Reliability Improvement Strategy of Medium Voltage Distribution Network Based on Network Frame Optimization." International Journal of Electrical Energy 7, no. 2 (2019): 58–61. http://dx.doi.org/10.18178/ijoee.7.2.58-61.

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Wang, Yifan, Hao Wang, Kaijie Wang, and Wei Zhang. "Cloud Gaming Video Coding Optimization Based on Camera Motion-Guided Reference Frame Enhancement." Applied Sciences 12, no. 17 (2022): 8504. http://dx.doi.org/10.3390/app12178504.

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Recent years have witnessed tremendous advances in clouding gaming. To alleviate the bandwidth pressure due to transmissions of high-quality cloud gaming videos, this paper optimized existing video codecs with deep learning networks to reduce the bitrate consumption of cloud gaming videos. Specifically, a camera motion-guided network, i.e., CMGNet, was proposed for the reference frame enhancement, leveraging the camera motion information of cloud gaming videos and the reconstructed frames in the reference frame list. The obtained high-quality reference frame was then added to the reference fra

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Lu, Hannan, Zixian Guo, and Wangmeng Zuo. "Modulated Memory Network for Video Object Segmentation." Mathematics 12, no. 6 (2024): 863. http://dx.doi.org/10.3390/math12060863.

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Existing video object segmentation (VOS) methods based on matching techniques commonly employ a reference set comprising historical segmented frames, referred to as ‘memory frames’, to facilitate the segmentation process. However, these methods suffer from the following limitations: (i) Inherent segmentation errors in memory frames can propagate and accumulate errors when utilized as templates for subsequent segmentation. (ii) The non-local matching technique employed in top-leading solutions often fails to incorporate positional information, potentially leading to incorrect matching. In this

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Morris, John H., Dhameliya Vijay, Steven Federowicz, Alexander R. Pico, and Thomas E. Ferrin. "CyAnimator: Simple Animations of Cytoscape Networks." F1000Research 4 (August 5, 2015): 482. http://dx.doi.org/10.12688/f1000research.6852.1.

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CyAnimator (http://apps.cytoscape.org/apps/cyanimator) is a Cytoscape app that provides a tool for simple animations of Cytoscape networks. The tool allows you to take a series of snapshots (CyAnimator calls them frames) of Cytoscape networks. For example, the first frame might be of a network shown from a ”zoomed out” viewpoint and the second frame might focus on a specific group of nodes. Once these two frames are captured by the tool, it can animate between them by interpolating the changes in location, zoom, node color, node size, edge thickness, presence or absence of annotations, etc. Th

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Morris, John H., Dhameliya Vijay, Steven Federowicz, Alexander R. Pico, and Thomas E. Ferrin. "CyAnimator: Simple Animations of Cytoscape Networks." F1000Research 4 (December 30, 2015): 482. http://dx.doi.org/10.12688/f1000research.6852.2.

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CyAnimator (http://apps.cytoscape.org/apps/cyanimator) is a Cytoscape app that provides a tool for simple animations of Cytoscape networks. The tool allows you to take a series of snapshots (CyAnimator calls them frames) of Cytoscape networks. For example, the first frame might be of a network shown from a ”zoomed out” viewpoint and the second frame might focus on a specific group of nodes. Once these two frames are captured by the tool, it can animate between them by interpolating the changes in location, zoom, node color, node size, edge thickness, presence or absence of annotations, etc. Th

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Biao, Shi Yong, Guo Feng, and Long Xiang. "Pedestrian Detection Based on SOM Neutral Network." Applied Mechanics and Materials 380-384 (August 2013): 3858–61. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3858.

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This paper presents a method of detecting pedestrians side in video frames of cluttered scenes. This detection technique is based on the idea of wavelet template and SOM neutral network. In order to make detection results more accurate and reduce computation cost, we combine background subtraction and frames difference to decide where pedestrians stand in a frame.

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Sangeeta, Sangeeta, Preeti Gulia, and Nasib Singh Gill. "Flow incorporated neural network based lightweight video compression architecture." Indonesian Journal of Electrical Engineering and Computer Science 26, no. 2 (2022): 939. http://dx.doi.org/10.11591/ijeecs.v26.i2.pp939-946.

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The sudden surge in the video transmission over internet motivated the exploration of more promising and potent video compression architectures. Though the frame prediction based hand designed techniques are performing well and widely used but the recent deep learning based researches in this domain provided further directions of pure deep learning based next generation codecs. As the bandwidth over the internet is varying, adaptive bit rate representation is more suitable for video quality adjustment in tune with bandwidth variation. The proposed architecture comprises of end to end trainable

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Sangeeta, Sangeeta, Preeti Gulia, and Nasib Singh Gill. "Flow incorporated neural network based lightweight video compression architecture." Indonesian Journal of Electrical Engineering and Computer Science 26, no. 2 (2022): 939–46. https://doi.org/10.11591/ijeecs.v26.i2.pp939-946.

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The sudden surge in the video transmission over internet motivated the exploration of more promising and potent video compression architectures. Though the frame prediction based hand designed techniques are performing well and widely used but the recent deep learning based researches in this domain provided further directions of pure deep learning based next generation codecs. As the bandwidth over the internet is varying, adaptive bit rate representation is more suitable for video quality adjustment in tune with bandwidth variation. The proposed architecture comprises of end to end trainable

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Devyatiyarov, D. V., and N. V. Melnik. "Structural Dynamics of Network Frames in the Context of the Legitimacy Crisis in Libyan Jamahiriya (based on the Internet comments)." NSU Vestnik. Series: Linguistics and Intercultural Communication 21, no. 3 (2023): 84–94. http://dx.doi.org/10.25205/1818-7935-2023-21-3-84-94.

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The article deals with the English Internet comments viewed as non-professional political discourse of everyday network communication. In these comments the videos on the legitimacy crisis in Libya in the early 2010s are discussed. Considering the array of commentary texts as a conceptual system, we study the non-professional political discourse related to the Libyan crisis in terms of frame analysis. Since the consequences of this crisis are felt in the world politics to this day, the users keep commenting on it regularly, it makes it possible to study the dynamics of the conceptual discursiv

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Xu, Huipu, and Yiteng Wang. "Target Detection Network for Underwater Image Based on Adaptive Anchor Frame and Re-parameterization." Journal of Physics: Conference Series 2363, no. 1 (2022): 012012. http://dx.doi.org/10.1088/1742-6596/2363/1/012012.

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For low target detection rate and inaccurate localization of most target detection networks in special underwater environments, we propose an underwater target detection algorithm with adaptive anchor frames. The adaptive anchor frame selection strategy differs from the traditional methods of manually designing anchor frames and obtaining anchor frames using the K-means clustering algorithm. Our method is based on the K-means clustering algorithm and consists of a grouping strategy and a dynamic K-value strategy. It can also automatically calculate the appropriate numbers of anchor boxes and l

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Piao, Jinhui, Shiyi Jin, Dong-Hyun Seo, Samuel Woo, and Jin-Gyun Chung. "MAC-Based Compression Ratio Improvement for CAN Security." Applied Sciences 13, no. 4 (2023): 2654. http://dx.doi.org/10.3390/app13042654.

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Information security in a controller area network (CAN) is becoming more important as the connections between a vehicle’s internal and external networks increase. Encryption and authentication techniques can be applied to CAN data frames to enhance security. To authenticate a data frame, a message authentication code (MAC) needs to be transmitted with the CAN data frame. Therefore, space for transmitting the MAC is required within the CAN frame. Recently, the Triple ID algorithm has been proposed to create additional space in the data field of the CAN frame. The Triple ID algorithm ensures eve

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