Plant species recognition methods using leaf image: Overview
Plant plays an important role in agricultural, industrial, medicine, environmental and
ecological protection. Recently, with global warming, biodiversity loss, rapid urban …
ecological protection. Recently, with global warming, biodiversity loss, rapid urban …
A new switching-delayed-PSO-based optimized SVM algorithm for diagnosis of Alzheimer's disease
In healthcare sector, it is of crucial importance to accurately diagnose Alzheimer's disease
(AD) and its prophase called mild cognitive impairment (MCI) so as to prevent degeneration …
(AD) and its prophase called mild cognitive impairment (MCI) so as to prevent degeneration …
[HTML][HTML] A review of visual descriptors and classification techniques used in leaf species identification
KK Thyagharajan, I Kiruba Raji - Archives of Computational Methods in …, 2019 - Springer
Plants are fundamentally important to life. Key research areas in plant science include plant
species identification, weed classification using hyper spectral images, monitoring plant …
species identification, weed classification using hyper spectral images, monitoring plant …
A fast non-negative latent factor model based on generalized momentum method
Non-negative latent factor (NLF) models can efficiently acquire useful knowledge from high-
dimensional and sparse (HiDS) matrices filled with non-negative data. Single latent factor …
dimensional and sparse (HiDS) matrices filled with non-negative data. Single latent factor …
Deep-reinforcement-learning-based images segmentation for quantitative analysis of gold immunochromatographic strip
Gold immunochromatographic strip (GICS) is a widely used lateral flow immunoassay
technique. A novel image segmentation method is developed in this paper for quantitative …
technique. A novel image segmentation method is developed in this paper for quantitative …
[HTML][HTML] Fusion estimation for multi-rate linear repetitive processes under weighted try-once-discard protocol
In this paper, the fusion estimation problem is studied for a class of discrete time-varying
multi-rate linear repetitive processes (LRPs) under weighted try-once-discard protocol. The …
multi-rate linear repetitive processes (LRPs) under weighted try-once-discard protocol. The …
Finite-time state estimation for delayed neural networks with redundant delayed channels
The finite-time state estimation issue is addressed in this paper for discrete time-delayed
neural networks (NNs). More than one communication channel is utilized to improve the …
neural networks (NNs). More than one communication channel is utilized to improve the …
[HTML][HTML] Plant leaf classification using multiple descriptors: A hierarchical approach
The present work proposes another path for classification of plant species from digital leaf
images. Plant leaves can have an assortment of unmistakable elements like green and non …
images. Plant leaves can have an assortment of unmistakable elements like green and non …
[HTML][HTML] State estimation under non-Gaussian Lévy and time-correlated additive sensor noises: A modified Tobit Kalman filtering approach
Abstract The Tobit Kalman filter (TKF) is a powerful tool in solving the state estimation
problem for linear systems with censored measurements. This paper is concerned with the …
problem for linear systems with censored measurements. This paper is concerned with the …
[HTML][HTML] Optimized threshold-based convolutional neural network for plant leaf classification: a challenge towards untrained data
The problem of identifying the plant type seems to be tough due to the altering leaf color,
and the variations in leaf shape overage. The plant leaf classification is very challenging and …
and the variations in leaf shape overage. The plant leaf classification is very challenging and …