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Found 5 papers, 5 papers with code
ROCT-Net: A new ensemble deep convolutional model with improved spatial resolution learning for detecting common diseases from retinal OCT images
This paper presents a new enhanced deep ensemble convolutional neural network for detecting retinal diseases from OCT images.
Wise-SrNet: A Novel Architecture for Enhancing Image Classification by Learning Spatial Resolution of Feature Maps
Our Experiments on images with 224*224 resolution increased the Top-1 accuracy between 2% to 8% on different datasets and models.
Detecting and Counting Pistachios based on Deep Learning
Our model is able to assign pistachios that turn and change their appearance (e. g., open-mouth pistachios that look closed-mouth) to each other so does not count them incorrectly.
A modified deep convolutional neural network for detecting COVID-19 and pneumonia from chest X-ray images based on the concatenation of Xception and ResNet50V2
In this paper, we have trained several deep convolutional networks with introduced training techniques for classifying X-ray images into three classes: normal, pneumonia, and COVID-19, based on two open-source datasets.
Sperm Detection and Tracking in Phase-Contrast Microscopy Image Sequences using Deep Learning and Modified CSR-DCF
With this method, the motility attribute has also been extracted, and then with the help of the deep convolutional network, we have achieved high accuracy in sperm detection.
