Devdiscourse

Advanced Hybrid Deep Learning Model Enhances Reliability of Automobile Fraud Detection Systems

Researchers from Universiti Tun Hussein Onn Malaysia and Chettinad Institute of Technology developed a Golden Eagle-Assisted ...
Phys.org

New approach improves accuracy of quantum chemistry simulations using machine learning

A new trick for modeling molecules with quantum accuracy takes a step toward revealing the equation at the center of a popular simulation approach, which is used in fundamental chemistry and materials ...
Scientific Research Publishing

Sunil, C.K., Jaidhar, C.D. and Patil, N. (2022) Cardamom Plant Disease Detection Approach Using EfficientNetV2. IEEE Access, 10, 789-804.

ABSTRACT: Agriculture is essential for humanity’s survival, and productivity is crucial in agriculture. Owing to its multiple nutrients, cherry has become an important fruit for daily consumption; ...
IEEE

UL-VAE: An Unsupervised Learning Approach for Zero-day Malware Detection Using Variational Autoencoder

Abstract: With the rapid growth of Internet of Things (IoT) technology, there is an increase in the dangers of malware attacks. The underlying threat in these attacks is invading people's privacy and ...
Bleeping Computer

NimDoor crypto-theft macOS malware revives itself when killed

North Korean state-backed hackers have been using a new family of macOS malware called NimDoor in a campaign that targets web3 and cryptocurrency organizations. Researchers analyzing the payloads ...
Frontiers

Deep learning-based feature selection for detection of autism spectrum disorder

Introduction: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by challenges in communication, social interactions, and repetitive behaviors. The heterogeneity of ...
Frontiers

Enhanced heart sound anomaly detection via WCOS: a semi-supervised framework integrating wavelet, autoencoder and SVM

Anomaly detection is a typical binary classification problem under the condition of unbalanced samples, which has been widely used in various fields of data mining. For example, it can help detect ...
IEEE

A Malware Detection Approach Using Malware Images and Autoencoders

Abstract: Most machine learning-based malware detection systems use various supervised learning methods to classify different instances of software as benign or malicious. This approach provides no ...