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Deep learning models can improve low-field MRI images for better clinical diagnoses

Image-to-image translation model LoHiResGAN. ....

Gorodenkoff Shutterstock , Neural Network Resnet , Generative Adversarial Networks , Scientific Reports , Residual Neural Network , Deep Learning , Magnetic Resonance Imaging , Vertebral Column ,

The 6 Best Pre-Trained Models for Work and Business

The 6 Best Pre-Trained Models for Work and Business
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Vggnet Visual Geometry Group Network , Resnet Residual Neural Network , Convolutional Neural Network Architecture , Bidirectional Encoder Representations , Generative Pre Trained Transformer , Text To Transfer Transformer , Residual Neural Network , Visual Geometry Group Network , Tensorflow Hub ,

"A COVID-19 X-ray image classification model based on an enhanced convo" by Ashwini Kumar Pradhan, Debahuti Mishra et al.

The classification of medical images is significant among researchers and physicians for the early identification and clinical treatment of many disorders. Though, traditional classifiers require more time and effort for feature extraction and reduction from images. To overcome this problem, there is a need for a new deep learning method known as Convolution Neural Network (CNN), which shows the high performance and self-learning capabilities. In this paper,to classify whether a chest X-ray (CXR) image shows pneumonia (Normal) or COVID-19 illness, a test-bed analysis has been carried out between pre-trained CNN models like Visual Geometry Group (VGG-16), VGG-19, Inception version 3 (INV3), Caps Net, DenseNet121, Residual Neural Network with 50 deep layers (ResNet50), Mobile-Net and proposed CNN classifier. It has been observed that, in terms of accuracy, the proposed CNN model appears to be potentially superior to others. Additionally, in order to increase the performance of the CNN cl ....

Convolution Neural Network , Geometry Group , Neural Network , Visual Geometry Group , Caps Net , Residual Neural Network , Hill Climbing Algorithm , Particle Swarm Optimization , Receiver Operating Characteristic Curve , Area Under , Covid 19 , Ill Climbing Algorithms , Image Classification , Ailored Convolutional Neural Network , X Ray Images ,

Identification of the Breach of Short-Term Rental Regulations in Irish Rent Pressure Zones

The housing crisis in Ireland has rapidly grown in recent years. To make a more significant profit, many landlords are no longer renting out their houses under long-term tenancies but under short-term tenancies. Regulating rentals in Rent Pressure Zones with the highest and rising rents is becoming a tricky issue. In this paper, we develop a breach identifier to check short-term rentals located in Rent Pressure Zones with potential breaches only using publicly available data from Airbnb (an online marketplace focused on short-term home-stays) and Irish government websites. First, we use a Residual Neural Network to filter out outdoor landscape photos that negatively impact identifying whether an owner has multiple rentals in a Rent Pressure Zone. Second, a Siamese Neural Network is used to compare the similarity of indoor photos to determine if multiple rental posts correspond to the same residence. Next, we use the Haversine algorithm to locate short-term rentals within a circle cente ....

San Francisco , United States , Airbnb Apis , Doris Chenguang Wu , Cork Council , A Siamese Neural Network , Office Of The Planning Regulator , Siamese Neural Network , National Planning Application Dataset , Neural Network , Neural Network Resnet , Short Term Tenancies , Residential Tenancies Board , Inside Airbnb , Rent Pressure Zones , Planning Regulator , Residual Neural Network , Rent Pressure , Rent Pressure Zone , Harmonized Index , Consumer Prices , Greater Dublin , Irish Rent Pressure Zones , Local Electoral Area Dataset , Planning Application , Principal Residence Identifier ,