The remote sensing image object detection has advanced significantly; yet, small object detection remains challenging due to their limited size and varying scales. Furthermore, real-world deployment ...

The National Geospatial-Intelligence Agency (NGA) and the Army’s 18th Airborne Corps in May successfully tested a prototype tool that uses imagery data ...

The proposed pneumonia diagnosis method based on the Fast-YOLO deep learning model integrates image enhancement techniques with network structure optimization, significantly improving the efficiency ...

Whole-mount 3D imaging at the cellular scale is a powerful tool for exploring complex processes during morphogenesis. In organoids, it allows examining tissue architecture, cell types, and morphology ...

Oriented object detection has attained remarkable progress in addressing the challenges associated with rotating invariant feature extraction. However, most existing object detection most existing ...

Zeng X. Unleashing the potential of exosome ncRNAs for early gastric cancer detection—a critical appraisal of machine learning approaches. … ...

CTSMamba is a multitask deep learning model trained on longitudinal CT images of neoadjuvant chemotherapy-treated locally advanced gastric cancer that accurately predicts lymph node metastasis and ...

Scientists have revealed that Convolutional Neural Networks (CNNs), a type of deep learning algorithm, demonstrate superior performance compared to conventional non-machine learning approaches when ...