Sufi K Sulaiman Joins 1cPlatform as CTO, Taking the Helm to Shape the Company’s Next Era of Intelligent Automation and ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

Abstract: Deep learning models in computer vision face challenges such as high computational resource demands and limited generalization in practical scenarios. To address these issues, this study ...

Abstract: We introduce a new perspective and a theory, called Quantum Vision (QV) theory in deep learning, for object recognition. The proposed theory is based on particle-wave duality of quantum ...

Computer vision continues to be one of the most dynamic and impactful fields in artificial intelligence. Thanks to breakthroughs in deep learning, architecture design and data efficiency, machines are ...

Introduction: Accurate and automated fruit classification plays a vital role in modern agriculture but remains challenging due to the wide variability in fruit appearances. Methods: In this study, we ...

This study introduces Popnet, a deep learning model for forecasting 1 km-gridded populations, integrating U-Net, ConvLSTM, a Spatial Autocorrelation module and deep ensemble methods. Using spatial ...

Researchers have developed a deep learning model called LSTM-SAM that predicts extreme water levels from tropical cyclones more efficiently and accurately, especially in data-scarce coastal regions, ...

Computer vision has emerged as one of the most transformative areas of artificial intelligence, with deep learning models driving unprecedented advancements in both theoretical understanding and ...