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fooladgar--fahimeh
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Total 8 records
| # | Type | Title | Author | Publisher | Pub. Year | Subjects | Call Number |
|---|---|---|---|---|---|---|---|
| 1 | مقاله | Learning strengths and weaknesses of classifiers for RGB-D semantic segmentation | Fooladgar, F. | IEEE Computer Society | 2015 |
3D scene understanding.
RGB-D segmentation. Semantic scene labeling. Computer vision. Image segmentation. Pixels. Random processes. Semantics. Three dimensional computer graphics. 3D scenes. Conditional random field. Contextual relationships. Feature vectors. Generation algorithm. Potential function. Semantic labeling. Semantic segmentation. Image processing. |
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| 2 | مقاله | Semantic segmentation of RGB-D images using 3D and local neighbouring features | Fooladgar, F. | Institute of Electrical and Electronics Engineers Inc, | 2015 |
RGB-D image segmentation.
Semantic scene labeling. Algorithms. Classification (of information) Computer vision. Decision trees. Image processing. Semantics. Three dimensional computer graphics. 3D features. Conditional random field. Discriminative features. Feature description. Probabilistic output. Random forest classifier. Scene understanding. Semantic segmentation. Image segmentation. |
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| 3 | مقاله | 3M2RNet: Multi-modal multi-resolution refinement network for semantic segmentation | Fooladgar, F. | Springer Verlag, | 2020 |
Deep learning.
RGB-D images. Semantic segmentation. Classification (of information) Decoding. Deep neural networks. Image segmentation. Neural networks. Semantic Web. Semantics. Signal encoding. Three dimensional computer graphics. Abstract representation. Convolutional neural network. Feature extractor. Robotic applications. Scene understanding. Training procedures. Computer vision. |
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| 4 | مقاله | Lightweight residual densely connected convolutional neural network | Fooladgar, F. | Springer, | 2020 |
Convolutional neural networks.
Deep learning. Efficient architecture. Image classification. Convolution. Network architecture. Computational operations. Embedded and mobile devices. Inference process. Proposed architectures. Software equipment. Special hardware. Specific hardware. State of the art. |
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| 5 | مقاله | A survey on indoor RGB-D semantic segmentation: from hand-crafted features to deep convolutional neural networks | Fooladgar, F. | Springer, | 2020 |
Deep learning.
Hand-crafted features. RGB-Depth images. Semantic segmentation. Deep neural networks. Image enhancement. Neural networks. Semantic Web. Semantics. Surveys. Comprehensive analysis. Convolutional neural network. Depth image. Microsoft kinect. Scene understanding. Semantic labeling. Image segmentation. |
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| 6 | پایان نامه | بخشبندی معنایی با سرپرست تصاویر RGB-Depth Supervised Semantic Segmentation of RGB-Depth Images | فولادگر، فهیمه Fooladgar, Fahimeh | دانشگاه صنعتی شریف | 1399 | بخش بندی معنایی Semantic Segmentation / شبکه عصبی کارآمد Efficient Neural Network / دوربین RGB-D RGB-D Camera / چکانش دانش Knowledge Distillation / همجوشی توجه محور Attention-Based Fusion / الگوریتم برچسب گذاری Labeling Algorithm |
19-53435
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| 7 | مقاله | Geometrical analysis of localization error in stereo vision systems | Fooladgar, F. | 2013 |
Cone intersection.
Quantization error. Extensive simulations. Geometrical analysis. Geometrical error analysis. Geometrical modeling. Localization errors. Object localization. Quantization errors. Stereo vision system. Charge coupled devices. Computer vision. Error analysis. Pinhole cameras. Pixels. Stereo vision. Uncertainty analysis. |
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| 8 | پایان نامه | اصول طراحی صندلی آشپزخانه ایرانی با رویکرد مهندسی کانسی Principles of Designing a Chair for Iranian Kitchen, Concerning Kansei Engineering Approach | خیاط اردستانی، فهیمه سادات Khyat Ardestani, Fahimeh Sadat | دانشگاه صنعتی شریف | 1391 | ارگونومی Ergonmics / اختلالات اسکلتی - عضلانی Musculoskeletal Disorders (MSDs) / روش OWAS Ovako Working Posture Analysis System (OWAS) Method / مهندسی کانسی Kansei Engineering / طراحی صندلی Chair Design |
01-44164
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