Tag: feature fusion

Researchers have introduced ResACNet, a lightweight convolutional neural network that fuses multi-feature vibration maps to achieve robust bearing fault diagnosis ...

Researchers have developed a feature fusion framework that improves plant leaf disease classification under blur and compression while revealing specific ...

A new detection framework called TriFocus-YOLO improves fabric defect detection accuracy and maintains real-time speed by integrating edge enhancement and ...

Engineers have developed a lightweight multi-scale neural network that uses component structural context to improve aerial defect detection across power ...

A new study reports three neural modules that cut computational cost by 26.7 percent while improving accuracy benchmarks for real-time ...

Researchers report an improved YOLO model that detects small PCB surface defects with 90.63% sensitivity while reducing model size and ...

Researchers report a lightweight detection model that improves small-drone recognition in complex backgrounds while sustaining real-time speeds on edge hardware.

A new framework uses ant colony optimization to configure a modified DeepLabV3+ network with a residual feature fusion module, reporting ...

A new YOLOv8-based algorithm called DARF improves visible-infrared object detection by enhancing shallow features and adaptively routing cross-modal information, achieving ...

PVFire-YOLO, a real-time detection framework with attention-enhanced multiscale fusion, reaches 87.4% mean average precision on a new photovoltaic fire dataset ...