Results 11 to 20 of about 1,984,141 (275)
Introducing Image Classification Efficacies
IEEE Access, 2021 Accuracy assessment is essential in all image classification-related fields, ranging from molecular imaging to earth observation. However, existing accuracy metrics are too sensitive to class imbalance or lack explicit interpretations for assessing ...
Guofan Shao, Lina Tang, Hao Zhang
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Eigenregions for image classification [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004 For certain databases and classification tasks, analyzing images based region features instead of image features results in more accurate classifications. We introduce eigenregions, which are geometrical features that encompass area, location, and shape properties of an image region, even if the region is spatially incoherent.
Clément Fredembach +2 more
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A novel CapsNet neural network based on MobileNetV2 structure for robot image classification
Frontiers in Neurorobotics, 2022 Image classification indicates that it classifies the images into a certain category according to the information in the image. Therefore, extracting image feature information is an important research content in image classification.
Jingsi Zhang +3 more
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Imaging Classification of Constipation
Journal of the Anus, Rectum and Colon, 2023 The diagnosis of patients with chronic constipation is very complicated. This study aimed to develop a simple imaging classification for the diagnosis of chronic constipation by abdominal computed tomography (CT).Sixty-two patients who underwent abdominal CT in our hospital between January and June 2022 were enrolled.
Ishimaru, Kei +11 more
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Trading via image classification [PDF]
Proceedings of the First ACM International Conference on AI in Finance, 2020 The art of systematic financial trading evolved with an array of approaches, ranging from simple strategies to complex algorithms all relying, primary, on aspects of time-series analysis. Recently, after visiting the trading floor of a leading financial institution, we noticed that traders always execute their trade orders while observing images of ...
Naftali Cohen +2 more
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EFFECT OF PANSHARPENED IMAGE ON SOME OF PIXEL BASED AND OBJECT BASED CLASSIFICATION ACCURACY [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 Classification is the most important method to determine type of crop contained in a region for agricultural planning. There are two types of the classification. First is pixel based and the other is object based classification method.
P. Karakus, H. Karabork
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NOVEL CLASSIFICATION UNCERTAINTY MEASUREMENT MODEL INTEGRATING SPATIAL INFORMATION FOR REMOTE SENSING IMAGE [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Remote sensing image classification has important applications in many fields. However, the uncertainty of remote sensing image classification results will reduce its application value and reliability in these applications.
Q. Zhang, P. Zhang, X. Hu
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IMAGE QUATY ASSESSMENT FOR VHR REMOTE SENSING IMAGE CLASSIFICATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 The data from remote sensing images are widely used for characterizing land use and land cover at present. With the increasing availability of very high resolution (VHR) remote sensing images, the remote sensing image classification becomes more and more
Z. Li +5 more
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HIGH RESOLUTION IMAGE CLASSIFICATION [PDF]
المجلة العراقية للعلوم الاحصائية, 2005 Classification is an important field with many applications. In particular, the classification of digital imagery has important applications in the mapping community.
Wasfi Taher Saalih
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Ferrograph image classification
CoRR, 2020 It has been challenging to identify ferrograph images with a small dataset and various scales of wear particle. A novel model is proposed in this study to cope with these challenging problems. For the problem of insufficient samples, we first proposed a data augmentation algorithm based on the permutation of image patches.
Peng Peng, Jiugen Wang
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