This study explores optimizing the Traveling Salesman Problem (TSP) using Q-Learning reinforcement learning. The proposed method builds a Q-table to learn the optimal path and employs dynamic programming for local opt...
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Models trained with adversarial attack can be significantly improved stability and performance when faced with new uncertain environment. In this paper, we propose the robust training framework based on Wasserstein SA...
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Adaptable sensors, circuits, and substrates are joined with unbending electronic parts to make adaptable flexible hybrid electronics (FHE). The printing of nanomaterials has benefits over the costly, multi-step, and b...
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This paper introduces a new multi-modal model based on the Transformer architecture and tensor product fusion strategy, combining BERT's text vectors and ViT's image vectors to classify students psychological ...
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Mobile robot localisation is the process of determining the robot locations within its environment. Applying data collection by sensors to achieve localisation is the most fundamental ability required by a mobile robo...
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This article discusses the application of machine vision technology in industrial scene recognition. The research uses deep learning algorithms, combined with computer vision technology, to build a scene recognition s...
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The detection algorithms for various engineering structure cracks often suffer from missed detections, false positives, and low accuracy. This paper proposes an improved crack detection model based on Yolov11, integra...
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Software document is a file that records the composition and workflow of software, and it is an important basis for software maintenance and development. At present, we have the source program of the rCore operating s...
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Fiber Bragg Grating (FBG) sensors are widely used for dual-parameter monitoring of strain and temperature. Traditional demodulation methods, however, are often complex and costly. In this work, we present a demodulati...
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