Results 31 to 40 of about 2,965,444 (278)
Pixel-Wise Fabric Defect Detection by CNNs Without Labeled Training Data
IEEE Access, 2020 Surface inspection is a necessary process of fabric quality control. However, it remains a challenging task owing to diverse types of defects, various patterns of fabric texture, and application requirements for detection speed.
Zhen Wang, Junfeng Jing
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Geostatistical semi-supervised learning for spatial prediction
Artificial Intelligence in Geosciences, 2022 Geoscientists are increasingly tasked with spatially predicting a target variable in the presence of auxiliary information using supervised machine learning algorithms.
Francky Fouedjio, Hassan Talebi
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Deep Contextualized Acoustic Representations For Semi-Supervised Speech Recognition
, 2020 We propose a novel approach to semi-supervised automatic speech recognition (ASR). We first exploit a large amount of unlabeled audio data via representation learning, where we reconstruct a temporal slice of filterbank features from past and future ...
Kirchhoff, Katrin +3 more
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PADI-web corpus: Labeled textual data in animal health domain
Data in Brief, 2019 Monitoring animal health worldwide, especially the early detection of outbreaks of emerging pathogens, is one of the means of preventing the introduction of infectious diseases in countries (Collier et al., 2008) [3].
Julien Rabatel +2 more
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DataThe detection of human activities is an important step in automated systems to understand the context of given situations. It can be useful for applications like healthcare monitoring, smart homes, and energy management systems for buildings.
Thomas Pfitzinger +3 more
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Audio Event Detection using Weakly Labeled Data
, 2016 Acoustic event detection is essential for content analysis and description of multimedia recordings. The majority of current literature on the topic learns the detectors through fully-supervised techniques employing strongly labeled data.
Gencoglu O. +12 more
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IEEE AccessWith the continuous improvement of digitization, the processing and analysis of massive data has become one of the hot issues. Soft computing technology, as an emerging machine intelligence technology, performs well in handling complex uncertainty ...
Chunhua Liang
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A Threshold-Control Generative Adversarial Network Method for Intelligent Fault Diagnosis
Complex System Modeling and Simulation, 2021 Fault diagnosis plays the increasingly vital role to guarantee the machine reliability in the industrial enterprise. Among all the solutions, deep learning (DL) methods have achieved more popularity for their feature extraction ability from the raw ...
Xinyu Li, Sican Cao, Liang Gao, Long Wen
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Handwriting Recognition of Historical Documents with few labeled data
, 2018 Historical documents present many challenges for offline handwriting recognition systems, among them, the segmentation and labeling steps. Carefully annotated textlines are needed to train an HTR system.
Chammas, Edgard +2 more
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Gradient Agreement Hinders the Memorization of Noisy Labels
Applied Sciences, 2023 The performance of deep neural networks (DNNs) critically relies on high-quality annotations, while training DNNs with noisy labels remains challenging owing to their incredible capacity to memorize the entire training set.
Shaotian Yan +3 more
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