By selecting the improved LeNet-5 proposed in this paper, the classical Convolutional Neural Network (CNN) and ResNetl01 as the basis to extract the network, and comparing the models, the detection ...

In this paper, ship detection methods for optical remote sensing images are studied based on deep learning. First, to meet the needs of ship detection research, according to the characteristics of ...

Deep learning has revolutionised the field of image analysis and object detection by enabling computational models to learn hierarchical representations from vast datasets. This paradigm, largely ...

Revisiting Multi-Task Learning with ROCK: a Deep Residual Auxiliary Block for Visual Detection Multi-Task Learning (MTL) is appealing for deep learning regularization. In this paper, we tackle a ...

Anomaly detection in images is rapidly emerging as a critical field in both industrial quality control and medical diagnostics. Leveraging deep learning techniques, researchers have developed ...

The AttendSeg deep learning model performs semantic segmentation at an accuracy that is almost on-par with RefineNet while cutting down the number of parameters to 1.19 million.

Anomaly detection: "Deep learning technique strives to recognize abnormal patterns which don't match the behaviors expected for a particular system, out of millions of different transactions.