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Found 13 papers, 1 papers with code
Bayesian Convolutional Neural Networks for Limited Data Hyperspectral Remote Sensing Image Classification
In this work, we use for HSRS image classification a special class of deep neural networks, namely a Bayesian neural network (BNN).
Pixel-wise Distance Regression for Glacier Calving Front Detection and Segmentation
In this work, we propose to mitigate the class-imbalance between the calving front class and the non-calving front class by reformulating the segmentation problem into a pixel-wise regression task.
On Mathews Correlation Coefficient and Improved Distance Map Loss for Automatic Glacier Calving Front Segmentation in SAR Imagery
Moreover, we propose an improvement to the distance map-based binary cross-entropy (BCE) loss function.
Synthetic Glacier SAR Image Generation from Arbitrary Masks Using Pix2Pix Algorithm
Supervised machine learning requires a large amount of labeled data to achieve proper test results.
Bayesian U-Net for Segmenting Glaciers in SAR Imagery
It is therefore important to precisely monitor the position of the calving front.
Glacier Calving Front Segmentation Using Attention U-Net
An essential climate variable to determine the tidewater glacier status is the location of the calving front position and the separation of seasonal variability from long-term trends.
The Effect of Various Strengths of Noises and Data Augmentations on Classification of Short Single-Lead ECG Signals Using Deep Neural Networks
Due to the multiple imperfections during the signal acquisition, Electrocardiogram (ECG) datasets are typically contaminated with numerous types of noise, like salt and pepper and baseline drift.
Classification of breast cancer histology images using transfer learning
Breast cancer is one of the leading causes of mortality in women.
Classification
Classification Of Breast Cancer Histology Images
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Hyper-Hue and EMAP on Hyperspectral Images for Supervised Layer Decomposition of Old Master Drawings
In this work, we propose an image processing pipeline that operates on hyperspectral images to separate such layers.
Semi-Automatic Algorithm for Breast MRI Lesion Segmentation Using Marker-Controlled Watershed Transformation
The proposed method achieved an average Dice coefficient of 0. 7808$\pm$0. 1729 and Jaccard index of 0. 6704$\pm$0. 2167.
GMM-Based Synthetic Samples for Classification of Hyperspectral Images With Limited Training Data
This synthetic data is sampled from a GMM fitted to each class of the limited training data.
Classification Of Hyperspectral Images
General Classification
+1
Image Registration for the Alignment of Digitized Historical Documents
In this work, we conducted a survey on different registration algorithms and investigated their suitability for hyperspectral historical image registration applications.
Sketch Layer Separation in Multi-Spectral Historical Document Images
High-resolution imaging has delivered new prospects for detecting the material composition and structure of cultural treasures.
