Deep learning approaches, particularly convolutional neural networks (CNNs) and other architectures, were used in 49 papers. These models excel at image-based tasks such as land cover classification, ...

In today's data-driven environment, Python has become the mainstream language in the fields of machine learning and data science due to its concise syntax, rich library support, and active community, ...

Abstract: One of the most significant and difficult issues in medical image processing is brain tumor segmentation (BTS) as human classification might cause improper diagnosis and prognosis.

Ambient Scientific has introduced the GPX10 Pro, a system-on-chip designed specifically for edge AI applications. The device ...

Department of Materials Science and Engineering, City University of Hong Kong, Kowloon 999077, Hong Kong China Department of Physics, City University of Hong Kong, Kowloon 999077, Hong Kong China ...

This is a general purpose aimbot, which uses a neural network for enemy/target detection. The aimbot doesn't read/write memory from/to the target process. It is essentially a "pixel bot", designed ...

🎨 RGB Color Classification with Deep Learning | Classify 11 colors from RGB values using neural networks | 88.8% accuracy | TensorFlow + OpenCV ...

Abstract: Particle image velocimetry (PIV) is a crucial technique in experimental fluid dynamics for non-invasively measuring the velocity components of flow fields. Deep learning methods applied to ...