Search Results for author:
Found 11 papers, 7 papers with code
Lacunarity Pooling Layers for Plant Image Classification using Texture Analysis
This work contributes to the evolving landscape of artificial neural network architectures by introducing a novel pooling layer that enriches the representation of spatial features.
Histogram Layers for Neural Engineered Features
These engineered features include local binary patterns and edge histogram descriptors among others and they have been shown to be informative features for a variety of computer vision tasks.
Histogram Layer Time Delay Neural Networks for Passive Sonar Classification
In this work, a novel method combines a time delay neural network and histogram layer to incorporate statistical contexts for improved feature learning and underwater acoustic target classification.
Quantitative Analysis of Primary Attribution Explainable Artificial Intelligence Methods for Remote Sensing Image Classification
We present a comprehensive analysis of quantitatively evaluating explainable artificial intelligence (XAI) techniques for remote sensing image classification.
Histogram Layers for Synthetic Aperture Sonar Imagery
Synthetic aperture sonar (SAS) imagery is crucial for several applications, including target recognition and environmental segmentation.
Possibilistic Fuzzy Local Information C-Means with Automated Feature Selection for Seafloor Segmentation
The chosen features and resulting segmentation from the image will be assessed based on a select quantitative clustering validity criterion and the subset of the features that reach a desired threshold will be used for the segmentation process.
Learnable Adaptive Cosine Estimator (LACE) for Image Classification
We compare our LACE to alternative state-of-the art softmax-based and feature regularization approaches.
Explainable Systematic Analysis for Synthetic Aperture Sonar Imagery
In this work, we present an in-depth and systematic analysis using tools such as local interpretable model-agnostic explanations (LIME) (arXiv:1602. 04938) and divergence measures to analyze what changes lead to improvement in performance in fine tuned models for synthetic aperture sonar (SAS) data.
Divergence Regulated Encoder Network for Joint Dimensionality Reduction and Classification
In order to better represent statistical texture information for remote-sensing image classification, in this paper, we investigate performing joint dimensionality reduction and classification using a novel histogram neural network.
Histogram Layers for Texture Analysis
We present a histogram layer for artificial neural networks (ANNs).
Comparison of Possibilistic Fuzzy Local Information C-Means and Possibilistic K-Nearest Neighbors for Synthetic Aperture Sonar Image Segmentation
In this paper, we compare the segmentation performance of a semi-supervised approach using PFLICM and a supervised method using Possibilistic K-NN.
