Global ETD Search

Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.

Results

Showing 1 to 8 of 8 for “"pascal voc"”.

  1. Deep Learning Models for Context-Aware Object Detection

    … ROI. Using comprehensive experiments on the PASCAL VOC 2007, we demonstrate the effectiveness of our design choices, the resulting system outperforms the baseline in most object classes, and reaches 57.5 mAP (mean Average Precision) on the PASCAL VOC 2007 test set in comparison with 55.6 mAP …

    vt Repository record for Deep Learning Models for Context-Aware Object Detection (opens in a new tab)

  2. Object Detection Using Vision Transformed EfficientDet

    … evaluations were conducted using the PASCAL VOC 2007 and 2012 datasets, widely acknowledged benchmarks for object detection. The integrated ViT-EfficientDet model achieved an impressive mean Average Precision (mAP) score of 86.27% when tested on the PASCAL VOC 2007 dataset, …

    iupui Repository record for Object Detection Using Vision Transformed EfficientDet (opens in a new tab)

  3. Semi-supervised universal yolov3-spp with GIoU loss for autonomous driving object detection under sunny and foggy weather

    … CPR-A containing the following datasets: COCO, Pascal VOC, and annotated RESIDE-β. RESIDE-β only contains foggy images captured from the real world while COCO ad Pascal VOC are general object detection datasets that contain mostly clear images. We then take advantage of unannotated images in our …

    uiuc Repository record for Semi-supervised universal yolov3-spp with GIoU loss for autonomous driving object detection under sunny and foggy weather (opens in a new tab)

  4. Reducing false positives for object detection

    … Experiments show competitive results on PASCAL VOC and COCO without any bells and whistles. Our codes are available at: https://github.com/bowenc0221/Decoupled-Classification-Refinement.

    uiuc Repository record for Reducing false positives for object detection (opens in a new tab)

  5. Datasets, features, learning, and models in visual recognition

    … The performance of this feature is tested using PASCAL VOC 2006 and 2007 datasets. This feature performs well; it consistently improves the performance of visual object classifiers, and is particularly effective when the training dataset is small. With more and more collected training data, …

    uiuc Repository record for Datasets, features, learning, and models in visual recognition (opens in a new tab)

  6. Improving few-shot object detection by saving and hallucinating examples

    … improvements over state of the art for COCO and PASCAL VOC in the very few-shot setting. This effect appears to be independent of the choice of classifier or dataset. However, under the very low-shot regime, even if all high IOU boxes are used to train the classifier, the variations are still …

    uiuc Repository record for Improving few-shot object detection by saving and hallucinating examples (opens in a new tab)

  7. Using the Internet for object image retrieval and object image classification

    … We test the performance of this feature using PASCAL VOC 2006 and 2007 datasets. Our feature performs well; it consistently improves the performance of visual object classifiers, and is particularly effective when the training dataset is small.

    uiuc Repository record for Using the Internet for object image retrieval and object image classification (opens in a new tab)

  8. Generation and analysis of segmentation trees for natural images

    This dissertation is about extracting as well as making use of the structure and hierarchy present in images. We develop a new low-level, multiscale, hierarchical image segmentation algorithm designed to detect image regions regardless of their shapes, sizes, and levels of interior homogeneity. We …

    uiuc Repository record for Generation and analysis of segmentation trees for natural images (opens in a new tab)