02660nam 2200673z- 450 991055728530332120210501(CKB)5400000000041187(oapen)https://directory.doabooks.org/handle/20.500.12854/68496(oapen)doab68496(EXLCZ)99540000000004118720202105d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierGlobal Vegetation and Land Surface Dynamics in a Changing ClimateBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 online resource (108 p.)3-0365-0502-4 3-0365-0503-2 Global ecosystem changes are influenced by a combination of natural and anthropogenic factors. Ongoing changes in rainfall, temperature, and carbon dioxide in the atmosphere can affect natural or managed vegetation, such as forest, grassland, or farmland. Moreover, anthropogenic pressures, such as forest clearing, cattle grazing, increasing infrastructural development, intensive management, and expansion of cropland, can contribute to ecosystem degradation. This collection presents a wide range of studies examining natural and anthropogenic drivers in diverse ecosystems in Africa, Asia, and North America.Research & information: generalbicsscadaptive capacityclimate changeclimate change adaptationclimate change vulnerabilityconservationdeterminants of climate change impactdroughtEast Africaexposurefiregrazingn/aNDVIordered probit regressionperceived impact of climate changephotosynthesisrandom forestresiliencesavannasensitivitysolar-induced chlorophyll fluorescencevegetationvegetation activityvegetation anomalywater stresswoody vegetationResearch & information: generalMondal Pinkiedt1324785McDermid Sonali ShuklaedtMondal PinkiothMcDermid Sonali ShuklaothBOOK9910557285303321Global Vegetation and Land Surface Dynamics in a Changing Climate3036297UNINA02538nam 2200709z- 450 991055779150332120220111(CKB)5400000000045473(oapen)https://directory.doabooks.org/handle/20.500.12854/77165(oapen)doab77165(EXLCZ)99540000000004547320202201d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierMachine Learning/Deep Learning in Medical Image ProcessingBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 online resource (132 p.)3-0365-2664-1 3-0365-2665-X Many recent studies on medical image processing have involved the use of machine learning (ML) and deep learning (DL). This special issue, "Machine Learning/Deep Learning in Medical Image Processing", has been launched to provide an opportunity for researchers in the area of medical image processing to highlight recent developments made in their fields with ML/DL. Seven excellent papers that cover a wide variety of medical/clinical aspects are selected in this special issue.Technology: general issuesbicsscairway volume analysisanimal rat modelsartificial intelligenceCADxclassification modelscolon cancercolon polypscomputed tomographyconvolutional neural networkconvolutional neural networkscoronary artery diseasedata augmentationdeep learninghandcraftedmachine learningmedical image segmentationmicroscopicn/aneoplasm metastasisOCToptical biopsyoral carcinomaovarian neoplasmspancreasprostate carcinomaradiation exposuresegmentationSPECT MPI scanstomographytransfer learningx-ray computedTechnology: general issuesNishio Mizuhoedt1297577Nishio MizuhoothBOOK9910557791503321Machine Learning3024568UNINA