3.327 hasil untuk machine learning
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Artikel Jurnal Teks lengkap
State of the Art in Defect Detection Based on Machine Vision
Abstract Machine vision significantly improves the efficiency, quality, and reliability of defect detection. In visual inspection, excellent optical illumination platforms and suitable image acquisition hardware are the prerequisites for obtaining high-quality images. Image processing and analysis…
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Artikel Jurnal Teks lengkap
Jet-images — deep learning edition
…or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to…
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Artikel Jurnal Teks lengkap
A comprehensive review on convolutional neural network in machine fault diagnosis
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Artikel Jurnal Teks lengkap
Deep Learning applications for COVID-19
This survey explores how Deep Learning has battled the COVID-19 pandemic and provides directions for future research on COVID-19. We cover Deep Learning applications in Natural Language Processing, Computer Vision, Life Sciences, and Epidemiology. We describe how each of these applications vary…
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Artikel Jurnal Teks lengkap
Graph Self-Supervised Learning: A Survey
Deep learning on graphs has attracted significant interests recently. However, most of the works have focused on (semi-) supervised learning, resulting in shortcomings including heavy label reliance, poor generalization, and weak robustness. To address these issues, self-supervised learning (SSL)…
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Artikel Jurnal Teks lengkap
Class-Incremental Learning: A Survey
…classes emerge from time to time in our ever-changing world, requiring a learning system to acquire new knowledge continually. Class-Incremental Learning (CIL) enables the learner to incorporate the knowledge of new classes incrementally and build a universal classifier among all seen classes…
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Artikel Jurnal Teks lengkap
Layerwise learning for quantum neural networks
Abstract With the increased focus on quantum circuit learning for near-term applications on quantum devices, in conjunction with unique challenges presented by cost function landscapes of parametrized quantum circuits, strategies for effective training are becoming increasingly important. In order…
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Artikel Jurnal Teks lengkap
Hierarchical graph learning for protein–protein interaction
…natural PPI hierarchy. Here we present a double-viewed hierarchical graph learning model, HIGH-PPI, to predict PPIs and extrapolate the molecular details involved. In this model, we create a hierarchical graph, in which a node in the PPI network (top outside-of-protein view) is a protein graph…
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Artikel Jurnal
Geometric deep learning of RNA structure
…predicting them computationally has proven challenging. We introduce a machine learning approach that enables identification of accurate structural models without assumptions about their defining characteristics, despite being trained with only 18 known RNA structures. The resulting scoring…
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Artikel Jurnal Teks lengkap
Transfer Learning With Adaptive Fine-Tuning
With the utilization of deep learning approaches, the key factors for a successful application are sufficient datasets with reliable ground truth, which are generally not easy to obtain, especially in the field of medicine. In recent years, this issue has been commonly addressed with the…
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Artikel Jurnal Teks lengkap
Transformer neural network for protein-specific de novo drug generation as a machine translation problem
Drug discovery for a protein target is a very laborious, long and costly process. Machine learning approaches and, in particular, deep generative networks can substantially reduce development time and costs. However, the majority of methods imply prior knowledge of protein binders, their…
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Artikel Jurnal Teks lengkap
Domain Adaptive Ensemble Learning
…problem. We propose a unified framework termed domain adaptive ensemble learning (DAEL) to address both problems. A DAEL model is composed of a CNN feature extractor shared across domains and multiple classifier heads each trained to specialize in a particular source domain. Each such classifier is…
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Artikel Jurnal Teks lengkap
Challenges and Opportunities in Machine-Augmented Plant Stress Phenotyping
…comparison with unaided visual measurement. The growing capabilities of machine learning (ML) methods in conjunction with image-based phenotyping can extract new insights from curated, annotated, and high-dimensional datasets across varied crops and stresses. We propose an overarching strategy for…
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