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Machine Intelligence Research
ISSN 1476-8186 · Springer Science+Business Media · 6 artikel di indeks
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Artikel Jurnal Teks lengkap
Deep Industrial Image Anomaly Detection: A Survey
Abstract The recent rapid development of deep learning has laid a milestone in industrial image anomaly detection (IAD). In this paper, we provide a comprehensive review of deep learning-based image anomaly detection techniques, from the perspectives of neural network architectures, levels of…
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Deep Gradient Learning for Efficient Camouflaged Object Detection
Abstract This paper introduces deep gradient network (DGNet), a novel deep framework that exploits object gradient supervision for camouflaged object detection (COD). It decouples the task into two connected branches, i.e., a context and a texture encoder. The essential connection is the…
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VLP: A Survey on Vision-language Pre-training
Abstract In the past few years, the emergence of pre-training models has brought uni-modal fields such as computer vision (CV) and natural language processing (NLP) to a new era. Substantial works have shown that they are beneficial for downstream uni-modal tasks and avoid training a new model from…
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YOLOP: You Only Look Once for Panoptic Driving Perception
Abstract A panoptic driving perception system is an essential part of autonomous driving. A high-precision and real-time perception system can assist the vehicle in making reasonable decisions while driving. We present a panoptic driving perception network (you only look once for panoptic (YOLOP))…
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Dynamic Event-triggered Control and Estimation: A Survey
Abstract The efficient utilization of computation and communication resources became a critical design issue in a wide range of networked systems due to the finite computation and processing capabilities of system components (e.g., sensor, controller) and shared network bandwidth. Event-triggered…
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Artikel Jurnal Teks lengkap
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
Abstract Deep neural networks (DNN) have achieved unprecedented success in numerous machine learning tasks in various domains. However, the existence of adversarial examples raises our concerns in adopting deep learning to safety-critical applications. As a result, we have witnessed increasing…