A Multi-Channel GASF-Based hyperspectral classification framework integrating feature enhancement and interpretability for green chili pepper quality assessment

Non-Destructive Three-Grade Assessment of Pepper Sunscald Using Hyperspectral Imaging and Spectral Feature Fusion Strategy

Pepper production in southern Xinjiang, China, is severely constrained by sunscald, a non-infectious physiological disorder caused by intense solar radiation and high temperatures that compromises fruit quality and yield stability. This study proposes a complementary multi-feature fusion framework integrating Principal...

Integrating Spectral‐Spatial Band‐Ratio Evaluation and RGB‐Hyperspectral Fusion for Damage Detection in Green Peppers

Rapid and accurate detection of damaged peppers is essential for quality assessment and intelligent sorting in modern agricultural production. This study developed a hyperspectral imaging–based framework for discriminating healthy and damaged green peppers using spectral information acquired within the 372.6–1039.6 nm...

UniConEt: A novel Hybrid Deep architecture for fine grained Land Use and Land Cover Classification Using Hyperspectral Imagery

In the rapidly developing field of Remote Sensing (RS), Land Use Land Cover (LULC) classification of Hyperspectral Images (HSI) is a fundamental yet challenging task. HSI is also challenging because of its high spectral dimensionality. Therefore, this research develops a comprehensive spectral and spatial classificatio...

A deep investigation of optimisers for hyperspectral image classification – an evaluative study

SpectroRes-Former: A Spectral–Spatial Residual Transformer with Quantum–Fisher Feature Selection for Hyperspectral Land-Cover Classification

Proper land-cover and deforestation classification is crucial in environmental protection, sustainable land use, and climate change. Nevertheless, the current deep learning and remote sensing models are usually limited by poor spectral-spatial feature integration, high computational complexity, and poor feature selecti...

Hyperspectral Grading of Rice Blast Severity (0–5) Using Regional Spectral-Angle Features and Heterogeneous Stacking (XGBSVMRF-SA)

Rice blast caused by Pyricularia oryzae progresses from symptom-free leaves to extensive tissue death, while neighboring severity grades often show similar spectra. This study developed XGBSVMRF-SA to integrate regional spectral-angle (SA) features with heterogeneous stacking of XGBoost 3.1.2, support vector machine, a...