Nature

Investigating performance and key factors for real-world deployment of grain image classification using convolutional neural networks

Accurate and efficient grain quality assessment is critical for making informed decisions throughout the grain value chain. Early detection of disease enables actions to mitigate spread and further ...
Nature

Multi-resolution transfer learning for tampered image classification using SE-enhanced fused-MBConv and optimized CNN heads

Recognition of forged images is a critical task in fields such as forensics and cybersecurity. Conventional techniques often struggle to accurately identify tampered images due to complex artifacts ...