State Key Laboratory of Soil Pollution Control and Safety, and Women’s Hospital, School of Medicine, Zhejiang University, Hangzhou 310058, China ...

Deep learning model for multi-label thoracic disease detection from chest X-ray images using ResNet-50 and Grad-CAM visualization on the NIH ChestXray14 dataset.

I have read the paper and it seemed to be a single-label multi-classification problem. But the code use BCE and sigmoid instead of crossEntropy and softmax. So does it mean that the patient may have ...

1 School of Electronics and Electrical Engineering, Zhengzhou University of Science and Technology, Zhengzhou, China 2 Department of Mechanical and Electrical Engineering, Henan Vocational College of ...

In an era of rapidly growing multimedia data, the need for robust and efficient classification systems has become critical, specifically the identification of class names and poses or styles. This ...

As consumers are becoming more conscious of their health and wellbeing, many are turning towards natural, ‘clean’ foods - foods with few additives, made up largely of natural ingredients. Driven in ...

Abstract: Multi-label classification deals with the problem where an instance is associated with multiple labels simultaneously. Most existing multi-label classification algorithms assume that the ...