Multi-object tracking (MOT) in crowded scenes presents challenges such as target occlusion and interference from similar objects. The detection models that rely on the target center as positive samples often struggle ...
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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.
Financial forecasting is the practice of using historical data and economic indicators to make predictions about future financial trends and outcomes. The vaporous and active nature of stock markets has attracted atte...
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In order to explore the research of computer network data security encryption technology. The author proposes a data encryption scheme that combines symmetric encryption algorithms with asymmetric encryption algorithm...
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In port operations, berthing procedures play a crucial role, with ship detection serving as the cornerstone for automation in berthing scenarios. Existing ship detection methods suffer from issues such as low accuracy...
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Environmental perception, including object recognition and distance estimation, is a crucial aspect in the field of computer vision. Although distance estimation has received relatively less attention compared to obje...
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Inspired by the mechanism of batch processing systems, this paper proposes a multi-level and multi-swarm particle swarm optimization (MMPSO) algorithm to alleviate the performance degradation caused by imbalances in e...
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Synthetic Aperture Radar (SAR) has been widely used in marine environmental monitoring. However, there are some challenges in the detection of oil spills based on SAR images. Existing oil spill detection methods inade...
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A soil-centric crop recommendation system recommends suitable crops utilizing vital soil attributes as input factors. This sophisticated system incorporates parameters like Nitrogen (N), Phosphorus (P), Potassium (K) ...
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This paper proposes a novel knowledge-based neural network approach that, in the absence of specific device SPICE models, can utilize the measured data of actual diode devices to map the existing diode coarse model to...
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