67 citations · 113 across the 11 of their papers we have counts for
6 papers · 1 filter
Spatial Transformer Network YOLO Model for Agricultural Object Detection
Yash Zambre, Ekdev Rajkitkul, Akshatha Mohan +1
Object detection plays a crucial role in the field of computer vision by autonomously locating and identifying objects of interest. The You Only Look Once (YOLO) model is an effect…
Lacunarity Pooling Layers for Plant Image Classification using Texture Analysis
Akshatha Mohan, Joshua Peeples
Pooling layers (e.g., max and average) may overlook important information encoded in the spatial arrangement of pixel intensity and/or feature values. We propose a novel lacunarity…
Histogram Layers for Neural Engineered Features
Joshua Peeples, Salim Al Kharsa, Luke Saleh +1
In the computer vision literature, many effective histogram-based features have been developed. These engineered features include local binary patterns and edge histogram descripto…
Histogram Layers for Synthetic Aperture Sonar Imagery
Joshua Peeples, Alina Zare, Jeffrey Dale +1
Synthetic aperture sonar (SAS) imagery is crucial for several applications, including target recognition and environmental segmentation. Deep learning models have led to much succe…
Learnable Adaptive Cosine Estimator (LACE) for Image Classification
Joshua Peeples, Connor McCurley, Sarah Walker +2
In this work, we propose a new loss to improve feature discriminability and classification performance. Motivated by the adaptive cosine/coherence estimator (ACE), our proposed met…
Possibilistic Fuzzy Local Information C-Means with Automated Feature Selection for Seafloor Segmentation
Joshua Peeples, Daniel Suen, Alina Zare +1
The Possibilistic Fuzzy Local Information C-Means (PFLICM) method is presented as a technique to segment side-look synthetic aperture sonar (SAS) imagery into distinct regions of t…