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Titlebook: Advanced Intelligent Computing Technology and Applications; 20th International C De-Shuang Huang,Chuanlei Zhang,Wei Chen Conference proceed

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41#
發(fā)表于 2025-3-28 18:28:02 | 只看該作者
Designing Real-Time Neural Networks by Efficient Neural Architecture Searchhe critical nature of these systems, the ability of CNNs to meet stringent timing constraints is as crucial as their accuracy. However, variability in CNN execution times can lead to time constraint violations, affecting system reliability. To address this, we introduce RetNAS, an efficient neural a
42#
發(fā)表于 2025-3-28 20:08:30 | 只看該作者
Uncertainty-Driven Multi-scale Feature Fusion Network for Real-Time Image Derainingng imaging devices struggle to address this issue in real-time. While most efforts leverage deep networks for image deraining and have made progress, their large parameter sizes hinder deployment on resource-constrained devices. Additionally, these data-driven models often produce deterministic resu
43#
發(fā)表于 2025-3-29 00:53:24 | 只看該作者
RAY-Net: A Motorcycle Helmet Detection Method Integrated Auxiliary Correctionsignificant task. However, this field currently faces two major challenges. Firstly, there is a lack of a comprehensive open-source dataset that encompasses challenging scenarios such as nighttime and rainy days. Secondly, the detection of motorcycles in motion is often disrupted by pedestrians and
44#
發(fā)表于 2025-3-29 03:16:46 | 只看該作者
Augmented Fuzzy Min-Max Neural Network Driven to Preprocessing Techniques and Space Search Optimizatsed. The purpose of this approach is to reduce the complexity of the hyperbox as well as to eliminate the hyperbox overlap problem. AFMNN consists of four stages, which are input layer, preprocessing layer, hyperbox generation layer and output layer. In preprocessing layer, important features are se
45#
發(fā)表于 2025-3-29 10:42:23 | 只看該作者
Building Change Detection Based on Fully Convolutional Network in High-Resolution Remote Sensing Imabased building change detection method (BFFGNet). Initially, to capture the fine difference features at various scales, the Feature Difference Enhancement (FDE) module is proposed for enhancing interaction of information between the bi-temporal features. Then, for extracting accurate boundary inform
46#
發(fā)表于 2025-3-29 11:36:47 | 只看該作者
Optimization of NUMA Aware DNN Computing Systemltaneous memory accesses facilitated by independent multiple processors. However, the efficacy of extensive computational tasks, including those in the realm of AI, hinges on the implementation of intricate memory allocation strategies within this framework. Consider the Linux operating system, wher
47#
發(fā)表于 2025-3-29 16:35:10 | 只看該作者
48#
發(fā)表于 2025-3-29 21:03:16 | 只看該作者
49#
發(fā)表于 2025-3-30 03:56:14 | 只看該作者
50#
發(fā)表于 2025-3-30 04:59:29 | 只看該作者
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