IEEE

A Dense Bootstrap Contrastive Learning Method With 3-D Dynamic Convolution for Few-Shot PolSAR Image Classification

Abstract: High-quality labeled samples of polarimetric synthetic aperture radar (PolSAR) images are relatively scarce. Therefore, achieving optimal classification performance with limited labeled ...
IEEE

CTNet: Multimodal Remote Sensing Image Keypoint Detection and Description for CNN and Transformer Architectures

Abstract: Keypoint detection and description from multisensor or multimodal images are fundamental to image registration and its downstream tasks. However, nonlinear radiometric differences, ...
IEEE

Adapting a Segmentation Foundation Model for Medical Image Classification

Abstract: Recent advancements in foundation models, such as the Segment Anything Model (SAM), have shown strong performance in various vision tasks, particularly image segmentation, due to their ...
IEEE

Classification of Music Genres based on Machine Learning SVM and CNN

Abstract: This study aims to compare the performance of two classification methods—Support Vector Machine (SVM) and Convolutional Neural Network (CNN)—in identifying music genres based on audio data ...
IEEE

Image Caption Generation using CNN and Transformers

Abstract: Image caption generation from the combination of computer vision with NLP is a critically important task for machines being able to describe images, and this project leverages the power of ...
IEEE

Multiscale Segmentation-Guided Fusion Network for Hyperspectral Image Classification

Abstract: Convolution Neural Networks (CNNs) have demonstrated strong feature extraction capabilities in Euclidean spaces, achieving remarkable success in hyperspectral image (HSI) classification ...
IEEE

WTC-HST: Wavelet Transform Convolutions and Hierarchical Spatial Transformers for Polarimetric SAR Image Classification

Abstract: Polarimetric synthetic aperture radar (PolSAR) image classification is an important task in remote sensing. However, due to its complex scattering mechanism and high-dimensional features, ...
IEEE

Brain Cancer MRI Classification using CNN Architectures with Grid Search Enhanced with Coordinate Ascent Optimization

Abstract: Magnetic resonance imaging (MRI) is an important tool for brain cancer diagnosis and classification. Combined with modern convolutional neural network (CNN) technology, it can effectively ...
IEEE

Performance Assessment of Machine Learning Algorithms for Yellow Rust Wheat Disease Classification with UAV RGB Images

Abstract: This paper proposes a workflow for the detection of yellow rust winter wheat disease from RGB images captured by Unmanned Aerial Vehicles, together with a sensitivity analysis against ...
IEEE

SpectralDINO: Dual Mixture-of-Subspaces Low-Rank Adaptation for Cross-Domain Hyperspectral Image Few-Shot Classification

Abstract: Recently, few-shot learning (FSL)-based methods have achieved impressive results in cross-domain hyperspectral classification. However, existing approaches often ignore differences in ...
IEEE

Automated Trash Detection and Classification Using CNN: A Deep Learning Approach

Abstract: A research project focuses on creating automated trash detection and classification through convolutional neural networks (CNNs) with an objective to improve waste management systems. The ...
IEEE

Adaptive Smooth Adversarial Learning for Cross-Domain Hyperspectral Image Classification

Abstract: Cross-domain classification has emerged as a widely employed method in remote sensing due to the challenges associated with obtaining labels for hyperspectral image (HSI). To address the ...