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The availability of unprecedented unsupervised training data, along with neural scaling laws, has resulted in an unprecedented surge in model size and compute requirements for serving/training large ...
In real-world applications, screen capturing represents a significant scenario where this process can induce substantial distortion to the original image. Previous methods for simulating ...
This article surveys the recent development of semiconductor memory technologies spanning from the mainstream static random-access memory, dynamic random-access memory, and flash memory toward ...
Beam hopping (BH) is a widely adopted technique in multi-beam satellite communication systems, and it can effectively improve the system capacity. However, conventional BH with full frequency reuse ...
Semantic segmentation is a fundamental task in computer vision. In multi-class scenarios, the abundance of categories, feature similarity across classes, class imbalance, and the complexity of feature ...
Data-driven deep learning techniques have made notable advancements in modeling electromagnetic scattering problems. However, its accuracy on the testing dataset can be heavily reduced when data ...
Orthogonal frequency division multiplexing (OFDM)-based integrated sensing and communication (ISAC) is promising for future sixth-generation mobile communication systems. For OFDM-based ISAC systems, ...
Multiview subspace clustering aims to discover the inherent structure of data by fusing multiple views of complementary information. Most existing methods first extract multiple types of handcrafted ...
Semi-supervised change detection (SSCD) has become increasingly important in remote sensing image (RSI) analysis due to the scarcity of labeled data. While state-of-the-art SSCD methods have achieved ...
With the rapid advancement of magnetic confinement fusion technology, High- Temperature Superconductors (HTS) have emerged as a cornerstone for compact and efficient tokamak systems due to their ...
Detecting objects from uncrewed aerial vehicles (UAVs) are often hindered by a large number of small objects, resulting in low detection accuracy. To address this issue, mainstream approaches ...
Object detection in autonomous driving scenarios represents a significant research direction within artificial intelligence. Real-time and accurate object detection and recognition are crucial in ...