Abstract Medical image processing algorithms have traditionally focused on a specific problem or disease per modality. This approach has continued with the wide-spread adoption of deep learning in the last …
Universal multi-modal deep network for classification and segmentation of medical images Read More »
Abstract Deep learning and convolutional neural network technologies are increasingly used in the problems of analysis, segmentation, and recognition of objects in images. In this article, a convolutional neural network …
Wildfire Segmentation on Satellite Images using Deep Learning Read More »
Abstract in this paper, we propose a deep learning approach for the segmentation of body parts in computer tomography (CT) localizer images. Such images pose dif[1]culties in the automatic image …
Abstract COVID-19 has caused a global pandemic and become the most urgent threat to the entire world. Tremendous efforts and resources have been invested in developing diagnosis, prognosis and treatment …
Abstract The intervention of AI technology and self-driving vehicles changed transportation systems. The current self-driving vehicles demand reliable and accurate information from various functional modules. One of the major modules …
Abstract License Plate Recognition is the most efficient and cost-effective technique used for vehicle identification purposes. Automatic license plate recognition (ALPR) is used for finding the location of the number …
Detection and Recognition of Multiple License Plate From Still Images Read More »
Abstract Automatic image segmentation is an essential step for many medical image analysis applications, include computer-aided radiation therapy, disease diagnosis, and treatment effect evaluation. One of the major challenges for …
High-Resolution Encoder–Decoder Networks for Low-Contrast Medical Image Segmentation Read More »
Abstract The multidisciplinary approach of artificial intelligence is revolutionizing the traditional technologies used in medical image computing, radiology imaging, medical diagnoses, and features based disease identification [1], [2]. In this …
Abstract Automatic image segmentation is an essential step for many medical image analysis applications, include computer-aided radiation therapy, disease diagnosis, and treatment effect evaluation. One of the major challenges for …
High-Resolution Encoder-Decoder Networks for Low-Contrast Medical Image Segmentation Read More »
Abstract: The pandemic of coronavirus disease 2019 (COVID-19) is spreading all over the world. Medical imaging such as X-ray and computed tomography (CT) plays an essential role in the global …
