This paper describes our proposal in the multi-organ plant identification task (LifeClef2017 challenge [8]). The objective of the challenge is to evaluate to what extent machine learning and computer vision can learn from noisy data compared to trusted data. To address the challenge, we employ our recent proposed hybrid generic-organ convolutional neural network, abbreviated HGO-CNN [11] to tra...

The leaves are one of the most important main sources used for plant identification. Because of this the ImageCLEF 2011 proposed a challenge based on leaf analysis for plant identification. This paper reports the experiment results of the IFSC/USP team in participating of this task. The main goal is investigate the performance of Complex Network method for feature extraction and classification ...

In the wake of Darwin's evolutionary ideas, mid-nineteenth century naturalists realized the shortcomings of the long established two-kingdom system of organismal classification. Placement in a natural scheme of Protozoa, Protophyta, Phytozoa and Bacteria, microorganisms that exhibited plant-like and animal-like characteristics but obviously differed in organization from larger plants and animal...

The study on aerial plant organs (leaves and stems) motions is reviewed. The history of observations and studies is put in the perspective of the ideas surrounding them, leading to a presentation of the current classification of these motions. After showing the shortcomings of such a classification, we present, following an idea of Darwin's, the various movements in a renewed and observation-ba...

Cloning of the maize rough dwarf virus genome: molecular confirmation of the plant-reovirus classification scheme and identification of two large nonoverlapping coding domains within a single genomic segment. Title Cloning of the maize rough dwarf virus genome: molecular confirmation of the plant-reovirus classification scheme and identification of two large nonoverlapping coding domains within...

The vegetation of Eshtehard salt marshes in Karaj was studied, using the Braun-Blanquet method. Sixty five relevés recorded in different salt habitats were analyzed by Analyse Factorielle des Correspondances (AFC) and Classification Ascendant Hierarchique (CAH) methods, using the Anaphyto software. In general, 11 plant associations determined in the area: Aeluropodetum littoralis, Artemisietum ...

We assessed the effectiveness of very high spatial resolution IKONOS imagery for mapping a top invasive woody plant, Pittosporum undulatum, in a Protected Area in S.Miguel Island. We developed a segmentation-based classification scheme. A strong separability between most important land cover classes and a high accuracy in supervised classification maps was achieved. Overall separability improve...

Using PCA based Bayesian Classification to monitor the real plant with different operated conditions is proposed. Since the process condition s are time-variant, as the PCA subspace cannot explain the data of new events, the PCA should be reperformed. In this work the method of updating Bayesian model is developed. Only the data of new events are trained in the newer subspace. The ability of PC...

Cloning of the maize rough dwarf virus genome: molecular confirmation of the plant-reovirus classification scheme and identification of two large nonoverlapping coding domains within a single genomic segment. Title Cloning of the maize rough dwarf virus genome: molecular confirmation of the plant-reovirus classification scheme and identification of two large nonoverlapping coding domains within...

The manual process of plant leaves disease detection takes more time to perform. To achieve successful classification results, a flawless feature extraction is required for model. Aiming at the localization diseased-plant leaves, this paper performs complex tasks like segmentation, and multi-disease using ‘improved extraction, classification’ models. Here, Adaptive Fusion K-Means Region Growing...