Deep Learning-Based Virtual Optical Image Generation and Its Application to Early Crop Mapping

Deep learning and its application to medical image segmentation

One of the most common tasks in medical imaging is semantic segmentation. Achieving this segmentation automatically has been an active area of research, but the task has been proven very challenging due to the large variation of anatomy across different patients. However, recent advances in deep learning have made it possible to significantly improve the performance of image recognition and sem...

construction and validation of translation metacognitive strategy questionnaire and its application to translation quality

like any other learning activity, translation is a problem solving activity which involves executing parallel cognitive processes. the ability to think about these higher processes, plan, organize, monitor and evaluate the most influential executive cognitive processes is what flavell (1975) called “metacognition” which encompasses raising awareness of mental processes as well as using effectiv...

Active Labeling in Deep Learning and Its Application to Emotion

Crop Land Change Monitoring Based on Deep Learning Algorithm Using Multi-temporal Hyperspectral Images

Change detection is done with the purpose of analyzing two or more images of a region that has been obtained at different times which is Generally one of the most important applications of satellite imagery is urban development, environmental inspection, agricultural monitoring, hazard assessment, and natural disaster. The purpose of using deep learning algorithms, in particular, convolutional ...

Learning a Virtual Codec Based on Deep Convolutional Neural Network to Compress Image

Although deep convolutional neural network has been proved to efficiently eliminate coding artifacts caused by the coarse quantization of traditional codec, it’s difficult to train any neural network in front of the encoder for gradient’s back-propagation. In this paper, we propose an end-to-end image compression framework based on convolutional neural network to resolve the problem of non-diff...