Hybrid convolutional neural network and selective state space model with integrated edge features for infrared small target detection

Key Points

• Enhanced detection accuracy is achieved with the hybrid algorithm, providing better performance than traditional methods.
• The convolutional neural network exhibited an accuracy rate of 95% for detecting small infrared targets during testing.
• Application of a selective state space model supports effective integration of image features, leading to refined detection outcomes.
• Improvements in infrared detection are highlighted, potentially influencing future applications in industrial and surveillance fields.