Modern malware programs employ sophisticated techniques to maintain persistent command and control (C2) communication with ...

One of the shared, fundamental goals of most chemistry researchers is the need to predict a molecule's properties, such as ...

TrainCheck uses training invariants to find the root cause of hard-to-detect errors before they cause downstream problems, ...

Advancements in biomedical technologies have significantly facilitated the diagnosis and monitoring of diseases. Nonetheless, traditional diagnostic ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

Novel machine learning algorithm can analyse microscope images of corroded metal surfaces to estimate corrosion severity ...

The disease is known for its strong association with climatic variables, especially excessive rainfall, high humidity, and ...

NewYork-Presbyterian researchers have developed a deep learning model that increases doctors' abilities to diagnose ...

Address the challenges posed by the diverse range of potato fruit defects, which encompass difficulties in detection and limited accuracy, an improved YOLOv8 potato disease detection algorithm is ...

Wastewater surveillance became a popular choice among public health officials looking to track rapid virus mutations and ...

Artificial intelligence and machine learning are transforming acute respiratory distress syndrome (ARDS) management, enabling ...

The unmanned aerial vehicle (UAV) encounters challenges in detecting similar small targets during target detection tasks. Consequently, the current target detection algorithms struggle to accurately ...