Relevant bibliographies by topics / Target feature weighting

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  1. Journal articles
  2. Dissertations / Theses
  3. Conference papers

Academic literature on the topic 'Target feature weighting'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 June 2024

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Journal articles on the topic "Target feature weighting"

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Wang, Shaona, Yang Liu, and Linlin Li. "Sparse Weighting for Pyramid Pooling-Based SAR Image Target Recognition." Applied Sciences 12, no. 7 (2022): 3588. http://dx.doi.org/10.3390/app12073588.

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In this study, a novel feature learning method for synthetic aperture radar (SAR) image automatic target recognition is presented. It is based on spatial pyramid matching (SPM), which represents an image by concatenating the pooling feature vectors that are obtained from different resolution sub-regions. This method exploits the dependability of obtaining the weighted pooling features generated from SPM sub-regions. The dependability is determined by the residuals obtained from sparse representation. This method aims at enhancing the weights of the pooling features generated in the sub-regions
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Rahman, Ibrahim, Christopher Hollitt, and Mengjie Zhang. "Contextual-based top-down saliency feature weighting for target detection." Machine Vision and Applications 27, no. 6 (2016): 893–914. http://dx.doi.org/10.1007/s00138-016-0754-x.

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Akmal, Akmal, Rinaldi Munir, and Judhi Santoso. "Automatic Weight of Color, Texture, and Shape Features in Content-Based Image Retrieval Using Artificial Neural Network." JOIV : International Journal on Informatics Visualization 7, no. 3 (2023): 665. http://dx.doi.org/10.30630/joiv.7.3.1184.

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Image retrieval is the process of finding images in the database that are similar to the query image by measuring how close the feature values of the query image are to other images. Image retrieval is currently dominated by approaches that combine several different representations or features. The optimal weight of each feature is needed in combining the image features such as color features, texture features, and shape features. In this study, we use a multi-layer perceptron artificial neural network (MLP) method to obtain feature weights automatically and simultaneously look for optimal wei
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Ma, Yapeng, Yuhan Liu, Zongxu Pan, and Yuxin Hu. "Method of Infrared Small Moving Target Detection Based on Coarse-to-Fine Structure in Complex Scenes." Remote Sensing 15, no. 6 (2023): 1508. http://dx.doi.org/10.3390/rs15061508.

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In the combat system, infrared target detection is an important issue worthy of study. However, due to the small size of the target in the infrared image, the low signal-to-noise ratio of the image and the uncertainty of motion, how to detect the target accurately and quickly is still difficult. Therefore, in this paper, an infrared method of detecting small moving targets based on a coarse-to-fine structure (MCFS) is proposed. The algorithm mainly consists of three modules. The potential target extraction module first smoothes the image through a Laplacian filter and extracts the prior weight
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Yu, Liqun, Lu Wang, and Yongxing Xu. "Combination of Joint Representation and Adaptive Weighting for Multiple Features with Application to SAR Target Recognition." Scientific Programming 2021 (May 24, 2021): 1–9. http://dx.doi.org/10.1155/2021/9063419.

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For the synthetic aperture radar (SAR) target recognition problem, a method combining multifeature joint classification and adaptive weighting is proposed with innovations in fusion strategies. Zernike moments, nonnegative matrix factorization (NMF), and monogenic signal are employed as the feature extraction algorithms to describe the characteristics of original SAR images with three corresponding feature vectors. Based on the joint sparse representation model, the three types of features are jointly represented. For the reconstruction error vectors from different features, an adaptive weight
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Ye, Yishan, Zhenmiao Deng, Pingping Pan, and Wei He. "Range-Spread Target Detection Networks Using HRRPs." Remote Sensing 16, no. 10 (2024): 1667. http://dx.doi.org/10.3390/rs16101667.

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Range-spread target (RST) detection is an important issue for high-resolution radar (HRR). Traditional detectors relying on manually designed detection statistics have their performance limitations. Therefore, in this work, two deep learning-based detectors are proposed for RST detection using HRRPs, i.e., an NLS detector and DFCW detector. The NLS detector leverages domain knowledge from the traditional detector, treating the input HRRP as a low-level feature vector for target detection. An interpretable NLS module is designed to perform noise reduction for the input HRRP. The DFCW detector t
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Yu, Jimin, Hui Wang, Shangbo Zhou, and Shun Li. "Infrared Target Detection Based on Interval Sampling Weighting and 3D Attention Head in Complex Scenario." Applied Sciences 14, no. 1 (2023): 249. http://dx.doi.org/10.3390/app14010249.

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Thermal infrared detection technology can enable night vision and is robust in complex environments, making it highly advantageous for various fields. However, infrared images have low resolution and high noise, resulting in limited detailed information being available about the target object. This difficulty is further amplified when detecting small targets, which are prone to occlusion. In response to these challenges, we propose a model for infrared target detection designed to achieve efficient feature representation. Firstly, an interval sampling weighted (ISW) module is proposed, which s
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Töllner, Thomas, Klaus Gramann, Hermann J. Müller, and Martin Eimer. "The Anterior N1 Component as an Index of Modality Shifting." Journal of Cognitive Neuroscience 21, no. 9 (2009): 1653–69. http://dx.doi.org/10.1162/jocn.2009.21108.

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Processing of a given target is facilitated when it is defined within the same (e.g., visual–visual), compared to a different (e.g., tactile–visual), perceptual modality as on the previous trial [Spence, C., Nicholls, M., & Driver, J. The cost of expecting events in the wrong sensory modality. Perception & Psychophysics, 63, 330–336, 2001]. The present study was designed to identify electrocortical (EEG) correlates underlying this “modality shift effect.” Participants had to discriminate (via foot pedal responses) the modality of the target stimulus, visual versus tactile (Experiment 1
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Ma, Sugang, Bo Zhao, Zhiqiang Hou, Wangsheng Yu, Lei Pu, and Lei Zhang. "Robust Visual Object Tracking Based on Feature Channel Weighting and Game Theory." International Journal of Intelligent Systems 2023 (July 31, 2023): 1–19. http://dx.doi.org/10.1155/2023/6731717.

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Although the discriminative correlation filter- (DCF)-based tracker improves tracking performance, some object representation issues can still be further optimized. On the one hand, the DCF tracker’s deep convolutional features contain many noisy channels, and assigning the same weights to multiple channels cannot distinguish the importance of different channels. On the other hand, a simple weighted fusion approach cannot fully utilize the benefits of different feature types. We propose a visual object tracking algorithm based on adaptive channel weighting and feature game fusion to solve thes
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Pollmann, S., K. Mahn, B. Reimann, et al. "Selective Visual Dimension Weighting Deficit after Left Lateral Frontopolar Lesions." Journal of Cognitive Neuroscience 19, no. 3 (2007): 365–75. http://dx.doi.org/10.1162/jocn.2007.19.3.365.

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The left lateral frontopolar (LFP) cortex showed dimension change-related activation in previous event-related functional magnetic resonance imaging studies of visual singleton feature search with non-brain-lesioned participants. Here, we tested the hypothesis that LFP actively supports changes of attention from the old to the new target-defining dimension in singleton feature search. Singleton detection was selectively slowed in this task when the target-defining dimension changed in patients with left LFP lesions, compared with patients with frontomedian lesions as well as with matched contr
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Dissertations / Theses on the topic "Target feature weighting"

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Musti, Utpala. "Synthèse acoustico-visuelle de la parole par sélection d'unités bimodales." Thesis, Université de Lorraine, 2013. http://www.theses.fr/2013LORR0003.

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Ce travail porte sur la synthèse de la parole audio-visuelle. Dans la littérature disponible dans ce domaine, la plupart des approches traite le problème en le divisant en deux problèmes de synthèse. Le premier est la synthèse de la parole acoustique et l'autre étant la génération d'animation faciale correspondante. Mais, cela ne garantit pas une parfaite synchronisation et cohérence de la parole audio-visuelle. Pour pallier implicitement l'inconvénient ci-dessus, nous avons proposé une approche de synthèse de la parole acoustique-visuelle par la sélection naturelle des unités synchrones bimod
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Hamdan, Hussam. "Sentiment analysis in social media." Thesis, Aix-Marseille, 2015. http://www.theses.fr/2015AIXM4356.

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Dans cette thèse, nous abordons le problème de l'analyse des sentiments. Plus précisément, nous sommes intéressés à analyser le sentiment exprimé dans les textes de médias sociaux.Nous allons nous concentrer sur deux tâches principales: la détection de polarité de sentiment dans laquelle nous cherchons à déterminer la polarité (positive, négative ou neutre) d'un texte donné et l'extraction de cibles d’opinion et le sentiment exprimé vers ces cibles (par exemple, pour le restaurant nous allons extraire des cibles comme la nourriture, pizza, service). Notre principal objectif est de construire d
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Musti, Utpala. "Synthèse acoustico-visuelle de la parole par sélection d'unités bimodales." Electronic Thesis or Diss., Université de Lorraine, 2013. http://www.theses.fr/2013LORR0003.

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Ce travail porte sur la synthèse de la parole audio-visuelle. Dans la littérature disponible dans ce domaine, la plupart des approches traite le problème en le divisant en deux problèmes de synthèse. Le premier est la synthèse de la parole acoustique et l'autre étant la génération d'animation faciale correspondante. Mais, cela ne garantit pas une parfaite synchronisation et cohérence de la parole audio-visuelle. Pour pallier implicitement l'inconvénient ci-dessus, nous avons proposé une approche de synthèse de la parole acoustique-visuelle par la sélection naturelle des unités synchrones bimod
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Conference papers on the topic "Target feature weighting"

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Zhang, Yinzhe, Guixi Liu, and Hongyan Duan. "Visual Target Tracking Based on Compressive Feature Weighting." In 2015 International Industrial Informatics and Computer Engineering Conference. Atlantis Press, 2015. http://dx.doi.org/10.2991/iiicec-15.2015.153.

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Chen, ShiWei, ShengXiu Zhang, XiaoGang Yang, and NaiXin Qi. "Contour Segment Feature Weighting in Infrared Automatic Target Recognition." In 2016 7th International Conference on Mechatronics, Control and Materials (ICMCM 2016). Atlantis Press, 2016. http://dx.doi.org/10.2991/icmcm-16.2016.1.

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Jiang, Yue, Yubing Han, and Weixing Sheng. "Target recognition of radar HRRP using manifold learning with feature weighting." In 2016 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition (iWEM). IEEE, 2016. http://dx.doi.org/10.1109/iwem.2016.7505053.

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Wang, Chenchen, Weimin Su, Hong Gu, and Jianchao Yang. "Multi-scale Convolution and Feature-weighting Network for Radar Target Recognition." In 2019 IEEE MTT-S International Microwave Biomedical Conference (IMBioC). IEEE, 2019. http://dx.doi.org/10.1109/imbioc.2019.8777825.

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Ståhlsten, Torbjörn, Hans C. Strifors, and Guillermo C. Gaunaurd. "Signature Features in Returned Echoes From Submerged Targets Insonified by Short, Broadband Pulses: Comparison of Experiments and Theory." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0421.

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Abstract Backscattered echoes are studied from submerged elastic targets in the frequency domain and combined time-frequency domain when the targets are insonified by short, broadband sound pulses. The targets are either an air-filled spherical shell or various solid brass or steel spheres. The incident waveform is generated by weighting a sinusoidal signal with a Blackman time-window of a few cycles width. The spectrum is computed from each recorded set of experimental data and the result is shown to agree well with the theoretical prediction for the corresponding target and interrogating wav
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Kaidarov, Almas, Andrey Magda, Andrey Samarin, Fuad Aliyev, and Zhanna Kazakbayeva. "Managed Pressure Drilling and Managed Pressure Cementing: First Successful Implementation of Advanced Technologies for Unique Wells with Constant Inflow in Slim Drill Project." In SPE Annual Caspian Technical Conference. SPE, 2022. http://dx.doi.org/10.2118/212108-ms.

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Abstract While drilling well in the Pre-Caspian basin, a presumably technogenic nature zone of influx was exposed, which did not fit into the model of the geological structure of the section. Attempts of influx management were unsuccessful. The well had to be abandoned without reaching the target. This article describes the experience of Managed Pressure Drilling and Cementing technologies deployment, process features and equipment hookup in unconventional wellhead configuration and Slim Drill type of rig. Application of MPD technology made reaching target depth successful in the condition of
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