Transfer Learning Based Fruits Image Segmentation for Fruit-Picking Robots

He, Yongfu; Pan, Fangfang; Wang, Baoyu; Teng, Ziqing; Wu, Jianhua

doi:10.1109/ccet50901.2020.9213127

Cited by 7 publications

(2 citation statements)

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“…The high computation power and long training time of NNs shape a burden. To overcome the, papers integrates transfer learning, a technique that adjusts a model trained for a different task instead of training from scratch [211,244,253,256,257]. Transfer learning proved to obtain effective results at reduced cost using the pretrained model.…”

Section: ) Challengesmentioning

confidence: 99%

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Technologies Driving the Shift to Smart Farming: A Review

Elbeheiry

Balog

2023

IEEE Sensors J.

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As today's agriculture industry is facing numerous challenges, including climate changes, encroachment of the urban environment and lack of qualified farmers, there is a need for new practices to ensure sustainable agriculture and food supply. Consequently, there is an emphasis on upgrading the farming practices by shifting towards Smart Farming (SF) -utilizing advanced information and communication technologies to improve the quantity and quality of the crop with minimal labor interference. SF has gained lots of interest in recent years utilizing a variety of technological innovations in the field, which imposes a challenge on farmers and technology integrators to identify the suitable technologies and best practices for a particular application. This paper provides a survey of the most recent SF scientific literature to identify common practices toward technology integration, challenges, and solutions. The survey was conducted on 588 papers published on the IEEE database following Cochrane methods to ensure appropriate analysis and interpretation of results. The papers' contributions were analyzed to identify necessary technologies that constitute SF, and consequently, research themes were identified. The identified themes are sensors, communication, big data, actuators and machines, and data analysis. Besides presenting an in-depth analysis of each identified theme, the paper discusses integrating more than one technology in systems to achieve independency. The most common SF systems are remote monitoring, autonomous, and intelligent decision-making systems.

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