Satellite networks can fill the blind areas of ground signal coverage of traditional communication networks, and it can provide safe and reliable communication services in remote areas and complex ...

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 ...

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 ...

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 ...

Accurately predicting the occurrence, amplitude, and propagation speed of traffic flow shockwaves are essential for dynamic traffic control to mitigate traffic congestion. However, traditional ...

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 ...

This study uses a hybrid deep learning technique to classify asphalt, pavement, and unpaved roads. In real-world circumstances, image data noise can damage image categorization algorithms. This issue ...