Abstract: This paper describes an AI-driven automated system that leverages Convolutional Neural networks (CNNs ... and compute hit rates for anomaly detection. InceptionResNetV2 model that achieved ...

faster and affordable detection of breast cancer cells. The technology - a novel semiconductor device-based biosensor model in computer simulation test - has been developed by NIT-R’s Prof ...

In the initial stage, endmember extraction and abundance map estimation are carried out using a convolutional autoencoder. An elliptical kernel is then applied to compute spectral distances and ...

autoencoder model built with TensorFlow/Keras to learn normal patterns from your metrics and identify deviations. The system includes scripts for data collection, preprocessing, model training, and ...

In this study, we applied the anomaly detection method based on sparse structure learning of the element correlation within MD trajectories to identify important features associated with state ...

This repository contains source code for CRAS implemented with PyTorch. CRAS aims to address inter-class interference and intra-class overlap in multi-class anomaly detection through center-aware ...

This paper describes the development of an algorithm for verification of signatures written on a touch-sensitive pad. The signature verification algorithm is based on an artificial neural network. The ...