The adaptability of an electromagnetic radiation measurement system in the explosive field environment of energetic materials is studied, the installation method of the instrument is demonstrated, and the measurement ...
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With the continuous decrease in the critical dimensions of integrated circuits, mask optimization has becomethe main challenge in VLSI design. In recent years, thriving machine learning has been gradually introduced i...
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With the continuous decrease in the critical dimensions of integrated circuits, mask optimization has becomethe main challenge in VLSI design. In recent years, thriving machine learning has been gradually introduced in the field ofoptical proximity correction (OPC). Currently, advanced learning-based frameworks have been limited by low mask printability or large computational overhead. To address these limitations, this paper proposes a learning-based frameworknamed SegNet-OPC, which can generate optimized masks from the target layout at shorter training and turnaround timewith higher mask printability. The proposed framework consists of a backbone network and loss terms suitable for maskoptimization tasks, followed by a fine-tuning network. The framework yields remarkable improvements over conventionalmethods, delivering significantly faster turnaround time and superior mask printability and manufacturability. With just1.25 hours of training, the framework achieves comparable mask complexity while surpassing the state-of-the-art methods,achieving a minimum 3% enhancement in mask printability and an impressive 16.7% improvement in mask manufacturability.
This research uses real-world images with complicated disturbance information (the backdrop was identical to the apples' surfaces) to identify and categorize apple quality. This research introduces a new model for...
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With the rapid development of urban transportation, vehicle re-identification has become a focal point in traffic management and vehicle tracking problems. In order to address the problem of small inter-class similari...
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Unspent Transaction Output (UTXO) is part of the transaction data set, which represents the digital cryptocurrency asset in transaction-based blockchain systems. The data management capability, storage method and occu...
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A machine learning (ML) framework is proposed to achieve the automatic and rapid optimization of antenna topologies. A convolutional neural network (CNN) is utilized as a surrogate model (SM) and is combined with rein...
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It is well-established that terrestrial communication systems may fail during emergencies such as earthquakes, tsunamis, and floods. Fortunately, with the rapid advancement of unmanned aerial vehicle (UAV) network tec...
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The Internet of Things' incorporation with healthcare systems has enabled new prospects in patient monitoring and healthcare management. This research work offers a new Internet of Things (IoT) enabled healthcare ...
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Cloud computing has been developed as a front-line platform for consumer and commercial potential. Additionally, it enables users to access data and apps from any location. Businesses will use cloud services to borrow...
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In cloud radio access networks, it is difficult to efficiently use the baseband unit resources. To improve resource utilisation, this paper proposes the Predictive Borrow and Lend method, which maps between baseband u...
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