Showing 1,161 - 1,180 results of 11,103 for search 'features problems', query time: 0.11s Refine Results
  1. 1161

    Adaptive Enhancement Algorithm of High-Resolution Satellite Image Based on Feature Fusion by Ruizhe Wang, Wang Xiao

    Published 2022-01-01
    “…Since the traditional adaptive enhancement algorithm of high-resolution satellite images has the problems of poor enhancement effect and long enhancement time, an adaptive enhancement algorithm of high-resolution satellite images based on feature fusion is proposed. …”
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  2. 1162

    A Moving Object Detection Method Based on Conditional Information and Feature Deepening by Hongrui Zhang, Luxia Yang

    Published 2025-01-01
    “…Next, a multiscale feature refinement module is devised to further explore the rich semantic information in the deep feature, thereby enhancing the feature representation capability of the network. …”
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  3. 1163
  4. 1164

    Research of dynamic gesture recognition based on multi-instance learning of kinematics features by Cai-qiu ZHOU, Yu-wang YANG, Hai-bo PANG

    Published 2017-11-01
    “…Compared to static gestures,dynamic gestures had some new characteristics.The problems of dynamic gestures recognition was spewed by using kinematics mode,such as divergence modes,curl modes,symmetric and ant-symmetric modes,the second and third principal invariant modes of the gradient tensor,the second and third principal invariant modes of the strain tensor and the third principal invariant modes of spin tensor; Further,a framework based on multi-instance learning was proposed,organize all these principle modes for each gesture were organized to a dynamic gestures bag-of-words,and the similarity between the mode of unknown type dynamic gestures and the all bag-of-words were calculated.Then,the nearest neighbor method was used to recognize the dynamic gestures.The experimental results show that the dynamic gestures recognition based on multi-instance kinematics features principal mode learning methods can obtain a higher recognition rate.…”
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  5. 1165
  6. 1166

    SOME FEATURES OF THE COMMERCIALIZATION OF RESEARCH WORK AND INNOVATION PROJECTS IN THE CONTEXT OF EURASIAN INTEGRATION by I. V. Medynskaya

    Published 2018-10-01
    “…The article examines the problems and prospects of the commercialization of innovations in the context of the Eurasian integration. …”
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  7. 1167
  8. 1168

    UFM: Unified feature matching pre-training with multi-modal image assistants. by Yide Di, Yun Liao, Hao Zhou, Kaijun Zhu, Qing Duan, Junhui Liu, Mingyu Lu

    Published 2025-01-01
    “…We present Multimodal Image Assistant (MIA) transformers, finely tunable structures adept at handling diverse feature matching problems. UFM exhibits versatility in addressing both feature matching tasks within the same modal and those across different modals. …”
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  9. 1169

    Special Features of Digitization of Archival Materials and Professional Issues Relevant to Digital Copies by Mojca Horvat, Miroslav Novak

    Published 2014-01-01
    “…Abstract Some special features should be identified when digitizing archival materials. …”
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  10. 1170
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  12. 1172

    Transformer-based multi-task learning for table tennis motion feature recognition by Tianfang Ma

    Published 2025-06-01
    “…In order to solve the above-mentioned problems, this paper proposes a novel table tennis motion feature recognition method based on Transformer-based multi-task learning. …”
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  13. 1173

    Speech Genre of Reminder and Discursive Conditioning of its Features in Virtual Pedagogical Discourse by T. G. Rabenko, E. S. Denisova, A. D. Chardyntseva

    Published 2023-06-01
    “…The study examines the genre-defining features of the speech genre “reminder” in virtual pedagogical discourse. …”
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  14. 1174

    FDTransUnet: An aluminum surface defect segmentation model based on feature differentiation. by Mingzhu Tang, Wencheng Wang

    Published 2025-01-01
    “…First, the limited defective samples are effectively expanded by the feature differentiation data augmentation strategy to alleviate the overfitting problem caused by the insufficient sample. …”
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  15. 1175
  16. 1176

    Unsupervised detection method of RoQ covert attacks based on multilayer features by Jing ZHAO, Jun LI, Chun LONG, Wei WAN, Jinxia WEI, Kai CHEN

    Published 2022-09-01
    “…To solve the problems that RoQ covert attacks are hidden in overwhelming background traffic and difficult to identify, besides the existing samples are scarce and cannot provide large-scale learning data, an unsupervised detection method of RoQ covert attacks based on multilayer features was proposed under the condition of very little prior knowledge.First, considering that most normal flow might interfere with subsequent results, a classification method based on semi-supervised spectral clustering was studied by flow characteristics, so that the proportion of normal samples in the filtered traffic was close to 100%.Secondly, in order to distinguish the nuance between the hidden attack features and normal flow without relying on the attack samples, an unsupervised detection model based on the n-Shapelet subsequence was constructed by packet characteristics, and the subsequences with obvious difference were used, which enabled detection of RoQ convert attacks.Experimental results demonstrate that with only a small number of learning samples, the proposed method has higher precision and recall rate than existing methods, and is robust to evading attacks.…”
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  17. 1177
  18. 1178

    Adaptive Particle Swarm Optimization with Landscape Learning for Global Optimization and Feature Selection by Khalil Abbal, Mohammed El-Amrani, Oussama Aoun, Youssef Benadada

    Published 2025-01-01
    “…We tested them on global optimization functions and the feature selection problem. The proposed method gives encouraging results, outperforming native PSO in almost all instances and remaining competitive with state-of-the-art methods.…”
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  19. 1179
  20. 1180

    Electronic Library Systems in the Focus of Digital Didactics and Cognitive Features of the Digital Generation by N. I. Gendina, E. V. Kosolapova

    Published 2024-05-01
    “…Representatives of this digital generation are integrated into digital society from their birth, so they have views, attitudes and values that differ from the worldview of older generations. The distinctive features and problems of developing the cognitive abilities of Z generation are considered. …”
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