Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 191 Document Number: D02960
Notes:
Website of International Public Relations Association. Article 134. 5 pages., Report of an award-winning public relations project in the Environmental category involving redevelopment of a small farming community in southeastern Turkey. Part of it involved encouraging production of saffron rather than cotton (which requires more water).
3 pages., Online from publisher website., Following a training course in technology stewardship, actors in the Caribbean's agri-food sector are implementing ICT approaches to provide agricultural advice and support to their local communities
This article is maintained in the office of the Agricultural Communications Program, University of Illinois > "International" section > "Philippines CARD Group" file folder., Brief summary of vital communications components of the Masagana Farm Program
22 pages, The objective of this study was to provide a comprehensive overview of the recent advancements in the use of deep learning (DL) in the agricultural sector. The author conducted a review of studies published between 2016 and 2022 to highlight the various applications of DL in agriculture, which include counting fruits, managing water, crop management, soil management, weed detection, seed classification, yield prediction, disease detection, and harvesting. The author found that DL’s ability to learn from large datasets has great promise for the transformation of the agriculture industry, but there are challenges, such as the difficulty of compiling datasets, the cost of computational power, and the shortage of DL experts. The author aimed to address these challenges by presenting his survey as a resource for future research and development regarding the use of DL in agriculture.
