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LeCun, Y. (1988) A Theoretical Framework for Back-Propagation. In: Touretzky, D., Hinton, G. and Sejnowski, T., Eds., Proceedings of the 1988 Connectionist Models Summer School, CMU, Pittsburg, PA.

has been cited by the following article:

• TITLE: Detection of “Swollen Shoot” Disease in Ivorian Cocoa Trees via Convolutional Neural Networks

  AUTHORS: Mamadou Coulibaly, Konan Hyacinthe Kouassi, Silue Kolo, Olivier Asseu

  KEYWORDS: Drone, Convolutional Neural Networks, Image Recognition, Feature Detection

  JOURNAL NAME: Engineering, Vol.12 No.3, March 12, 2020

  ABSTRACT: Recent advances in diagnostics have made image analysis one of the main areas of research and development. Selecting and calculating these characteristics of a disease is a difficult task. Among deep learning techniques, deep convolutional neural networks are actively used for image analysis. This includes areas of application such as segmentation, anomaly detection, disease classification, computer-aided diagnosis. The objective which we aim in this article is to extract information in an effective way for a better diagnosis of the plants attending the disease of “swollen shoot”.