Results 231 to 240 of about 11,444,505 (290)
Integrating Kolmogorov-Arnold networks and sparse attention for robust visual plant disease symptom identification across diverse agricultural crops. [PDF]
Shen Y +7 more
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ZDAM: a new deep learning model for bean leaf disease diagnosis. [PDF]
Liu J +9 more
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Risk factors associated with meiotic errors in blastocysts with mosaic results on biopsy. [PDF]
Liu J +21 more
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ALSDet: a global context-enhanced network for detecting small-target diseases on apple leaves. [PDF]
Gong X, Xu P, Ren R, Gong F, Zhang S.
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Gene-Specific Endothelial Programs Drive AVM Pathogenesis in <i>SMAD4</i> and <i>ALK1</i> Loss-of-Function. [PDF]
Oppenheim O +7 more
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Volumetric Imaging of Ex Vivo Oral Mucosa Specimens with Multi-Scale Wide Field-of-View Optical Coherence Tomography/Microscopy in Near-Infrared-II Window. [PDF]
Chueh CB +5 more
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Mosaicing of Microscope Images
Digital Image Computing: Techniques and Applications (DICTA'05), 2005Image mosaicing has found a number of applications such as panoramic imaging, digital terrain mapping, ophthalmology, and virtual microscopy. In this paper, we present an automated mosaicing technique for generating mosaics from microscope images. We carry out robust image feature matching and global geometric and radiometric parameter estimation.
Changming Sun +3 more
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SPIE Proceedings, 2005
Most consumer-level digital cameras use a color filter array to capture color mosaic data followed by demosaicking to obtain full-color images. However, many sophisticated demosaicking algorithms are too complex to implement on-board a camera. To use these algorithms, one must transfer the mosaic data from the camera to a computer without introducing ...
Kapil A. Chaudhari, Stanley J. Reeves
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Most consumer-level digital cameras use a color filter array to capture color mosaic data followed by demosaicking to obtain full-color images. However, many sophisticated demosaicking algorithms are too complex to implement on-board a camera. To use these algorithms, one must transfer the mosaic data from the camera to a computer without introducing ...
Kapil A. Chaudhari, Stanley J. Reeves
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Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170), 2002
If it is impossible to capture all the image in one scan with the available equipment, a montage can be made from separately scanned pieces. We describe an automatic mosaicing process for document images. The image shifts are found by a correlation technique, using an image pyramid and sequential similarity to reduce computation time.
Adrian P. Whichello, Hong Yan 0001
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If it is impossible to capture all the image in one scan with the available equipment, a montage can be made from separately scanned pieces. We describe an automatic mosaicing process for document images. The image shifts are found by a correlation technique, using an image pyramid and sequential similarity to reduce computation time.
Adrian P. Whichello, Hong Yan 0001
openaire +2 more sources
ACM Transactions on Graphics, 2002
This paper introduces a new kind of mosaic, called Jigsaw Image Mosaic (JIM), where image tiles of arbitrary shape are used to compose the final picture. The generation of a Jigsaw Image Mosaic is a solution to the following problem: given an arbitrarily-shaped container image and a set of arbitrarily-shaped image tiles, fill the container as compactly
J. Kim, PELLACINI, FABIO
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This paper introduces a new kind of mosaic, called Jigsaw Image Mosaic (JIM), where image tiles of arbitrary shape are used to compose the final picture. The generation of a Jigsaw Image Mosaic is a solution to the following problem: given an arbitrarily-shaped container image and a set of arbitrarily-shaped image tiles, fill the container as compactly
J. Kim, PELLACINI, FABIO
openaire +1 more source

