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Bioinoculants with Nano-compounds to Improve Soil Health: A Step Toward Sustainable Agriculture
In recent decades, agrochemicals have enhanced crop productivity to meet increasing global food requirements. However, prolonged and extensive use of agrochemicals has resulted in contamination that persists in the soil system which can be biomagnified in the food chain. Furthermore, toxic chemicals adversely affect important soil microbial biota, the key drivers of biogeochemical cycles. This concern has raised the need to develop environmentally friendly and cost-effective nano- and micro-biotechnology strategies to minimize the adverse impact of agrochemicals and pesticide residues on soil microbiota, soil fertility, and their biomagnification in food crops. Nano-bioinoculants - the combi...
Human Development Report 1999
Published for the United Nations Development Programme (UNDP).
Ah Q and Others
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Advances in Building Energy Research
Advances in Building Energy Research (ABER) offers state-of-the-art information on the environmental science and performance of buildings, linking new technologies and methodologies with the latest research on systems, simulations and standards. As stringently reviewed as a journal but with the breadth of a book, this annual volume brings together invited contributions from the foremost international experts on energy efficiency and environmental quality of buildings. Spanning a broad range of technical subjects, this is a 'must have' reference on global developments in the field, suitable for architects and building engineers, environmental engineers, industry professionals, students, teach...
View Synthesis Using Stereo Vision
Image-based rendering, as an area of overlap between computer graphics and computer vision, uses computer vision techniques to aid in sythesizing new views of scenes. Image-based rendering methods are having a substantial impact on the field of computer graphics, and also play an important role in the related field of multimedia systems, for applications such as teleconferencing, remote instruction and surgery, virtual reality and entertainment. The book develops a novel way of formalizing the view synthesis problem under the full perspective model, yielding a clean, linear warping equation. It shows new techniques for dealing with visibility issues such as partial occlusion and "holes". Furthermore, the author thoroughly re-evaluates the requirements that view synthesis places on stereo algorithms and introduces two novel stereo algorithms specifically tailored to the application of view synthesis.
Interactive Theorem Proving
This book constitutes the refereed proceedings of the 8th International Conference on Interactive Theorem Proving, ITP 2017, held in Brasilia, Brazil, in September 2017. The 28 full papers, 2 rough diamond papers, and 3 invited talk papers presented were carefully reviewed and selected from 65 submissions. The topics range from theoretical foundations to implementation aspects and applications in program verification, security and formalization of mathematical theories.
Computer Vision - ECCV'98
This two-volume set constitutes the refereed proceedings of the 5th European Conference on Computer Vision, ECCV'98, held in Freiburg, Germany, in June 1998. The 42 revised full papers and 70 revised posters presented were carefully selected from a total of 223 papers submitted. The papers are organized in sections on multiple-view geometry, stereo vision and calibration, geometry and invariances, structure from motion, colour and indexing, grouping and segmentation, tracking, condensation, matching and registration, image sequences and video, shape and shading, motion and flow, medical imaging, appearance and recognition, robotics and active vision, and motion segmentation.
Mathematical Aspects of Deep Learning
In recent years the development of new classification and regression algorithms based on deep learning has led to a revolution in the fields of artificial intelligence, machine learning, and data analysis. The development of a theoretical foundation to guarantee the success of these algorithms constitutes one of the most active and exciting research topics in applied mathematics. This book presents the current mathematical understanding of deep learning methods from the point of view of the leading experts in the field. It serves both as a starting point for researchers and graduate students in computer science, mathematics, and statistics trying to get into the field and as an invaluable reference for future research.
