ScholarIQanswers from OpenAlex
Computers and Electronics in Agriculture
JournalCitation impact & published research
Computers and Electronics in Agriculture is a journal indexed in ScholarIQ from OpenAlex.
How many works does Computers and Electronics in Agriculture have?
ScholarIQindexed works
Computers and Electronics in Agriculture has 11,071 works in the ScholarIQ index. The count is the OpenAlex total, not the number of papers listed on this page.
How many citations does Computers and Electronics in Agriculture have?
ScholarIQcitation count
Computers and Electronics in Agriculture has 437,084 citations in the OpenAlex counts ScholarIQ stores.
What is the h-index of Computers and Electronics in Agriculture?
ScholarIQh-index
Computers and Electronics in Agriculture has an h-index of 221 in OpenAlex.
What is the article processing charge of Computers and Electronics in Agriculture?
ScholarIQarticle processing charge
Computers and Electronics in Agriculture lists an article processing charge of 3,680 USD in OpenAlex.
What is the OpenAlex record for Computers and Electronics in Agriculture?
ScholarIQopenalex
The OpenAlex for Computers and Electronics in Agriculture is on the source record.
What are the most-cited papers on Computers and Electronics in Agriculture?
ScholarIQmost cited works
Using deep transfer learning for image-based plant disease identification
Junde Chen, Jinxiu Chen, Defu Zhang, Yuandong Sun, Yaser A. Nanehkaran
Monitoring plant diseases and pests through remote sensing technology: A review
Jingcheng Zhang, Yanbo Huang, Ruiliang Pu, Pablo González‐Moreno, Lin Yuan, Kaihua Wu, Wenjiang Huang
Deep feature based rice leaf disease identification using support vector machine
Prabira Kumar Sethy, Nalini Kanta Barpanda, Amiya Kumar Rath, Santi Kumari Behera
Deep convolutional neural networks for mobile capture device-based crop disease classification in the wild
Artzai Picón, Aitor Álvarez-Gila, Maximiliam Seitz, Amaia Ortiz‐Barredo, Jone Echazarra, Alexander Johannes
A recognition method for cucumber diseases using leaf symptom images based on deep convolutional neural network
Juncheng Ma, Keming Du, Feixiang Zheng, Lingxian Zhang, Zhihong Gong, Zhongfu Sun