Deep learning-based object identification technology has numerous uses, including facial recognition, commercial analytics, and medical imaging analysis. An object detector has a backbone for ...

The target assignment in multi-unmanned aerial vehicle (multi-UAV) cooperative reconnaissance is a classic problem in weapon-target assignment. Despite the significance of the problem, most of the ...

In the energy transition towards sustainability, photovoltaic power is increasingly valued for its eco-friendly and renewable attributes. Northern and northwestern China’s deserts, abundant in solar ...

What is CNN in Deep Learning? In this video, we understand what is CNN in Deep Learning and why do we need it. CNN (or ...

With the development of deep learning, convolutional neural network is mainstream in face recognition but has two problems: poor recognition accuracy due to neglecting global semantic and key feature ...

Automatic building detection from satellite imagery plays a crucial role in rapidly developing areas. Building detection can assist in illegal building detection, population estimation, and so on.

While convolution and self-attention mechanisms have dominated architectural design in deep learning, this survey examines a fundamental yet understudied primitive: the Hadamard product. Despite its ...

This paper aims to explore seven commonly used optimization algorithms in deep learning: SGD, Momentum-SGD, NAG, AdaGrad, RMSprop, AdaDelta, and Adam. Based on an overview of their theories and ...

Advanced Persistent Threat (APT) is a highly targeted, complex, and long-term attack targeting specific organizations or individuals, aimed at stealing sensitive data or disrupting operations. APT is ...

The random volatility and uncertainty of renewable energy generation pose significant challenges to the energy management and optimal operation of microgrids, making this a hot topic in academic ...

In this paper, we introduce a four-phase method for converting BPMN diagrams into Solidity code using a new algorithm. Our approach aims to provide a comprehensive guide for this conversion process, ...

The optimization methods and deep neural network algorithms are considered for the analysis of load balancing. The tasks in the cloud are optimized using optimization algorithms for formulating the ...