Results 31 to 40 of about 2,018,951 (327)
Survey of Zero-Shot Image Classification
Jisuanji kexue yu tansuo, 2021 It is time-consuming and laborious to manually label a large number of samples, and samples from some rare classes are difficult to obtain. Therefore, the zero-shot image classification has become a research hotspot in the computer vision field. Firstly,
LIU Jingyi, SHI Caijuan, TU Dongjing, LIU Shuai
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Evaluation of Deep Learning on an Abstract Image Classification Dataset
, 2017 Convolutional Neural Networks have become state of the art methods for image classification over the last couple of years. By now they perform better than human subjects on many of the image classification datasets.
Rodriguez-Sanchez, Antonio +1 more
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Adversarial Reconstruction-Classification Networks for PolSAR Image Classification
Remote Sensing, 2019 Polarimetric synthetic aperture radar (PolSAR) image classification has become more and more widely used in recent years. It is well known that PolSAR image classification is a dense prediction problem. The recently proposed fully convolutional networks (
Yanqiao Chen +5 more
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Remote Sensing, 2022 Marine activities occupy an important position in human society. The accurate classification of ships is an effective monitoring method. However, traditional image classification has the problem of low classification accuracy, and the corresponding ship ...
Yantong Chen +4 more
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Fusing image representations for classification using support vector machines
, 2009 In order to improve classification accuracy different image representations are usually combined. This can be done by using two different fusing schemes.
Cherifi, Hocine, Demirkesen, Can
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Deep Learning Based Mineral Image Classification Combined With Visual Attention Mechanism
IEEE Access, 2021 Mineral image classification technology based on machine vision is an efficient system for ore sorting. With the development of artificial intelligence and computer technology, the deep learning-based mineral image classification system is gradually ...
Yang Liu +4 more
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Multiple Instance Learning for Heterogeneous Images: Training a CNN for Histopathology
, 2018 Multiple instance (MI) learning with a convolutional neural network enables end-to-end training in the presence of weak image-level labels. We propose a new method for aggregating predictions from smaller regions of the image into an image-level ...
CT Hiley +9 more
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Classification images with uncertainty
Journal of Vision, 2006 Classification image and other similar noise-driven linear methods have found increasingly wider applications in revealing psychophysical receptive field structures or perceptual templates. These techniques are relatively easy to deploy, and the results are simple to interpret.
Bosco S, Tjan, Anirvan S, Nandy
openaire +2 more sources
Fine-graind Image Classification via Combining Vision and Language
, 2017 Fine-grained image classification is a challenging task due to the large intra-class variance and small inter-class variance, aiming at recognizing hundreds of sub-categories belonging to the same basic-level category.
He, Xiangteng, Peng, Yuxin
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Asymptomatic infection poses a significant risk for children undergoing hematopoietic stem cell transplantation (HSCT). Pre‐transplant surveillance computed tomography (CT) is commonly used to identify occult infection, though its diagnostic yield remains uncertain.
Tyler Obermark +9 more
wiley +1 more source