Principal Data Engineer Rajesh Mattaparthi is using transformer-based AI to detect hidden faults in standby power generators ...
A new development in data science has given one popular machine learning tool an improved sense of place, enabling it to make ...
Humans have been successfully trained to spot AI-generated faces in a study led by researchers at the Australian National ...
Abstract: Due to the advantages of deep learning, in this paper, a regularized deep feature extraction (FE) method is presented for hyperspectral image (HSI) classification using a convolutional ...
BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
The ESC-50 dataset is a labeled collection of 2000 environmental audio recordings suitable for benchmarking methods of environmental sound classification. The dataset consists of 5-second-long ...
The code repository for "Feature Boosting and Compression for Class-Incremental Learning " [paper] (ECCV22) in PyTorch. If you use any content of this repo for your work, please cite the following bib ...
Service-based organizations may handle thousands of customer emails daily, placing a significant burden on IT help desks, customer service organizations, and other departments involved in reading, ...
1 Department of Computer Science, Rutgers University, New Brunswick, NJ, USA. 2 Department of Computer Science, Rochester Institute of Technology, Rochester, NY, USA. This paper presents a ...
Deep learning-based classification of eye diseases using Convolutional Neural Network for OCT images
Deep learning shows promising results in extracting useful information from medical images. The proposed work applies a Convolutional Neural Network (CNN) on retinal images to extract features that ...
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