Intelligent Imaging and AnalysisDaeEun Kim, Dosik Hwang Imaging and analysis are widely involved in various research fields, including biomedical applications, medical imaging and diagnosis, computer vision, autonomous driving, and robot controls. Imaging and analysis are now facing big changes regarding intelligence, due to the breakthroughs of artificial intelligence techniques, including deep learning. Many difficulties in image generation, reconstruction, de-noising skills, artifact removal, segmentation, detection, and control tasks are being overcome with the help of advanced artificial intelligence approaches. This Special Issue focuses on the latest developments of learning-based intelligent imaging techniques and subsequent analyses, which include photographic imaging, medical imaging, detection, segmentation, medical diagnosis, computer vision, and vision-based robot control. These latest technological developments will be shared through this Special Issue for the various researchers who are involved with imaging itself, or are using image data and analysis for their own specific purposes. |
Common terms and phrases
accuracy achieve addition algorithm analysis angle applied approach authors automatic background body boundary brain bubble calculated camera classification color combined compared comparison complexity Computer Conference convolutional corresponding CrossRef dataset deep depth detection distribution edge effect efficiency enhancement Equation error estimation evaluation experiments extraction feature filtering follows frame function IEEE Trans improved increase initial input inspection International layers learning light machine matrix mean measurement mesh method neural network noise normal object obtained operation optimization original parameters Pattern performance pixels pool position presented problem Proceedings proposed proposed method PubMed rail Recognition reconstruction Reference region registration represents respectively retrieval samples segmentation selection semantic shape shown in Figure shows sketch step structure surface Table technique term texture transform U-net vector visual volume Wang weight weld window