Agriculture has been the key to human development and farming technology has witnessed revolutionary changes over the years. Modern day farming is complex and is deemed so because

it requires the right combination of all the significant features such as rainfall, soil quality, seed quality, diseases and so on for a successful outcome. Precision farming is essential to confront the challenges of agricultural production.

While traditional research in the field aims at resolving fundamental issues, advancements in technology are now offering unconventional solutions to a variety of problems in the agricultural domain. The ability to find factors, which will boost produce requires analysis of enormous amount of data. This data needs to be stored and processed in real time and this is undoubtedly, what agriculture needs now. This is where deep learning (DL) can prove beneficial.

DL techniques are being applied to a spectrum of agricultural problems such as “disease detection/ identification, fruit/plants classification and fruit counting among other domains”. Integrating DL with autonomous robotic platforms has the possibility of revolutionizing agricultural practices. Several studies indicate the proficiency of DL with results of a high accuracy and precision in contrast to conventional techniques. The table below highlights cutting edge work in the field.