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Titlebook: Microbial Toxins in Foods and Feeds; Cellular and Molecul Albert E. Pohland,Vulus R. Dowell,Morris E. Potter Book 1990 Plenum Press, New Yo

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書目名稱Microbial Toxins in Foods and Feeds
副標(biāo)題Cellular and Molecul
編輯Albert E. Pohland,Vulus R. Dowell,Morris E. Potter
視頻videohttp://file.papertrans.cn/634/633064/633064.mp4
圖書封面Titlebook: Microbial Toxins in Foods and Feeds; Cellular and Molecul Albert E. Pohland,Vulus R. Dowell,Morris E. Potter Book 1990 Plenum Press, New Yo
出版日期Book 1990
關(guān)鍵詞Aflatoxin; Metabolite; Seafood; algae; development; microbial toxin; toxin
版次1
doihttps://doi.org/10.1007/978-1-4613-0663-4
isbn_softcover978-1-4612-7916-7
isbn_ebook978-1-4613-0663-4
copyrightPlenum Press, New York 1990
The information of publication is updating

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Merlin S. BergdollThis rose slowly to 760,000 in 1951 and then with increasing speed to 4.5 million in 1955. 1953 was the watershed year. Between March 1953 and 1954 over 1 million new licences were issued and the figures continued to grow at a comparable rate, reaching 8 million in 1958 and 12 million by 1963. The m
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Stephen B. Calderwood,John J. MekalanosThis rose slowly to 760,000 in 1951 and then with increasing speed to 4.5 million in 1955. 1953 was the watershed year. Between March 1953 and 1954 over 1 million new licences were issued and the figures continued to grow at a comparable rate, reaching 8 million in 1958 and 12 million by 1963. The m
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Bibhuti R. DasGuptaropagate the segmentation information between images in order to detect foreground objects in all these images simultaneously, under the hypothesis of using categorized or uncategorized images, rather than resorting to image co-segmentation that forces the use of similar categorized images. In fact,
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Randall K. Holmes,Edda M. Twiddy,Carol L. Pickett,Hilda Marcus,Michael G. Jobling,Francoise M. J. Pes a comprehensive annotated training set from different maritime environments. Creating such a dataset is expensive and time?consuming. To automate this process, this paper proposes a novel self?learning framework which automatically finetunes a generic pre-trained model to any new environment. With
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Yoichi Kamata,Shunji Kozakiropagate the segmentation information between images in order to detect foreground objects in all these images simultaneously, under the hypothesis of using categorized or uncategorized images, rather than resorting to image co-segmentation that forces the use of similar categorized images. In fact,
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