| Some good practices for applying convolutional neural networks to buried threat detection in Ground Penetrating Radar D Reichman, LM Collins, JM Malof Advanced Ground Penetrating Radar (IWAGPR), 2017 9th International Workshop …, 2017 | 74 | 2017 |
| Improving convolutional neural networks for buried target detection in ground penetrating radar using transfer learning via pretraining J Bralich, D Reichman, LM Collins, JM Malof Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXII …, 2017 | 60 | 2017 |
| A large-scale multi-institutional evaluation of advanced discrimination algorithms for buried threat detection in ground penetrating radar JM Malof, D Reichman, A Karem, H Frigui, KC Ho, JN Wilson, WH Lee, ... IEEE Transactions on Geoscience and Remote Sensing 57 (9), 6929-6945, 2019 | 43 | 2019 |
| Tiling and stitching segmentation output for remote sensing: Basic challenges and recommendations B Huang, D Reichman, LM Collins, K Bradbury, JM Malof arXiv preprint arXiv:1805.12219, 2018 | 39 | 2018 |
| On choosing training and testing data for supervised algorithms in ground-penetrating radar data for buried threat detection D Reichman, LM Collins, JM Malof IEEE Transactions on Geoscience and Remote Sensing 56 (1), 497-507, 2017 | 33 | 2017 |
| Improvements to the Histogram of Oriented Gradient (HOG) prescreener for buried threat detection in ground penetrating radar data D Reichman, LM Collins, JM Malof Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXII …, 2017 | 18 | 2017 |
| Target localization and signature extraction in GPR data using expectation-maximization and principal component analysis D Reichman, KD Morton Jr, LM Collins, PA Torrione Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX …, 2014 | 16 | 2014 |
| Improving the histogram of oriented gradient feature for threat detection in ground penetrating radar by implementing it as a trainable convolutional neural network JM Malof, J Bralich III, D Reichman, LM Collins Detection and Sensing of Mines, Explosive Objects, and Obscured Targets …, 2018 | 11 | 2018 |
| Algorithm development for deeply buried threat detection in GPR data D Reichman, JM Malof, LM Collins Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXI …, 2016 | 11 | 2016 |
| Target signature localization in GPR data by jointly estimating and matching templates D Reichman, KD Morton Jr, JM Malof, LM Collins, PA Torrione Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX …, 2015 | 11 | 2015 |
| Learning improved pooling regions for the histogram of oriented gradient (HOG) feature for Buried Threat Detection in Ground Penetrating Radar D Reichman, LM Collins, JM Malof Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXII …, 2017 | 10 | 2017 |
| How do we choose the best model? The impact of cross-validation design on model evaluation for buried threat detection in ground penetrating radar JM Malof, D Reichman, LM Collins Detection and Sensing of Mines, Explosive Objects, and Obscured Targets …, 2018 | 9 | 2018 |
| Tiling and stitching segmentation output for remote sensing: basic challenges and recommendations (2018) B Huang, D Reichman, LM Collins, K Bradbury, JM Malof arXiv preprint arXiv:1805.12219 3, 1805 | 9 | 1805 |
| Reliable training of convolutional neural networks for GPR-based buried threat detection using the Adam optimizer and batch normalization S Jacobson, D Reichman, J Bjornstad, LM Collins, JM Malof Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV …, 2019 | 8 | 2019 |
| Dense labeling of large remote sensing imagery with convolutional neural networks: a simple and faster alternative to stitching output label maps B Huang, D Reichman, LM Collins, K Bradbury, JM Malof arXiv preprint arXiv:1805.12219, 2018 | 8 | 2018 |
| Discriminative dictionary learning to learn effective features for detecting buried threats in ground penetrating radar data JM Malof, D Reichman, LM Collins Detection and sensing of mines, explosive objects, and obscured targets XXII …, 2017 | 7 | 2017 |
| The effect of translational variance in training and testing images on supervised buried threat detection algorithms for ground penetrating radar D Reichman, LM Collins, JM Malof Advanced Ground Penetrating Radar (IWAGPR), 2017 9th International Workshop …, 2017 | 6 | 2017 |
| Sampling training images from a uniform grid improves the performance and learning speed of deep convolutional segmentation networks on large aerial imagery B Huang, D Reichman, LM Collins, K Bradbury, JM Malof IGARSS, 2018 | 5 | 2018 |
| Tiling and Stitching Segmentation Output for Remote Sensing: Basic Challenges and Recommendations. arXiv 2019 B Huang, D Reichman, LM Collins, K Bradbury, JM Malof arXiv preprint arXiv:1805.12219, 0 | 5 | |
| An exploration of gradient-based features for buried threat detection using a handheld ground penetrating radar E Stump, D Reichman, LM Collins, JM Malof Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV …, 2019 | 3 | 2019 |
Leslie M CollinsProfessor of Electrical and Computer Engineering, Duke University確認したメール アドレス: duke.edu
