4.7 Article

Developing an automated monitoring system for fast and accurate prediction of soil texture using an image-based deep learning network and machine vision system

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Review Computer Science, Theory & Methods

Deep Learning-based Text Classification: A Comprehensive Review

Shervin Minaee et al.

Summary: This article provides a comprehensive review of over 150 deep learning-based models for text classification developed in recent years. It discusses their technical contributions, similarities, and strengths, as well as summarizes popular datasets used for text classification. The article also includes a quantitative analysis of the performance of different deep learning models on popular benchmarks and discusses future research directions.

ACM COMPUTING SURVEYS (2022)

Article Automation & Control Systems

Regularizing extreme learning machine by dual locally linear embedding manifold learning for training multi-label neural network classifiers

Mohammad Rezaei-Ravari et al.

Summary: Multi-label learning methods are regularized via Locally Linear Embedding (LLE) to increase efficiency, with experiments showing that using dual-manifold learning as the training method for neural classifiers significantly improves classification performance.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2021)

Article Agriculture, Multidisciplinary

Improved digital image-based assessment of soil aggregate size by applying convolutional neural networks

Pendar Alirezazadeh et al.

Summary: In this study, a convolutional neural network called SoilNet was used to classify images of different soil aggregate sizes taken from varying heights. The performance of pre-trained CNNs decreased as image resolution decreased with increasing photography height. SoilNet showed better performance on classifying images captured at higher heights.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2021)

Article Computer Science, Artificial Intelligence

Dual-manifold regularized regression models for feature selection based on hesitant fuzzy correlation

Mahla Mokhtia et al.

Summary: This paper introduces three novel frameworks for feature selection based on Ridge, LASSO, and Elastic Net regression methods, utilizing dual-manifold learning and hesitant fuzzy correlation (HFC). The frameworks calculate hesitant fuzzy correlation matrices (HFCMs) to select suitable features, and experiments confirm their effectiveness.

KNOWLEDGE-BASED SYSTEMS (2021)

Article Computer Science, Artificial Intelligence

Reliability assessment of water quality index based on guidelines of national sanitation foundation in natural streams: integration of remote sensing and data-driven models

Mohammad Najafzadeh et al.

Summary: The study employed four different Data-Driven Models to predict the Water Quality Index (WQI) for Karun River, with the FS-M5 MT model demonstrating the best performance in WQI classification estimation. According to the reliability analysis of WQI, there is only a 19% chance for a specimen from Karun River to have a better quality index.

ARTIFICIAL INTELLIGENCE REVIEW (2021)

Article Energy & Fuels

Waste management using an automatic sorting system for carrot fruit based on image processing technique and improved deep neural networks

Ahmad Jahanbakhshi et al.

Summary: This study addresses the classification of carrot fruit using improved deep neural networks, showing that convolutional neural networks provide a straightforward approach with increased accuracy. Comparing the proposed CNN algorithm with other classification methods demonstrates a 99.43% accuracy using the BN-CNN method.

ENERGY REPORTS (2021)

Article Biology

Detection of fraud in ginger powder using an automatic sorting system based on image processing technique and deep learning

Ahmad Jahanbakhshi et al.

Summary: This study aims to improve the accuracy of ginger powder classification by enhancing the pooling function in CNN and using BN technique, which could effectively prevent fraud in ginger powder.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

Article Biology

Learning-to-augment strategy using noisy and denoised data: Improving generalizability of deep CNN for the detection of COVID-19 in X-ray images

Mohammad Momeny et al.

Summary: This study introduces a data augmentation strategy by determining the type and value of noise density to improve the robustness and generalization of deep convolutional neural networks for COVID-19 detection. By utilizing learning-to-augment and denoised X-ray images approaches, new training data is generated and fine-tuned in various networks, leading to superior results compared to existing methods.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

Article Biology

A novel method based on machine vision system and deep learning to detect fraud in turmeric powder

Ahmad Jahanbakhshi et al.

Summary: Evaluating the quality of food and spices is crucial, especially when it comes to high-value spices like turmeric. Researchers have been exploring the use of computer vision methods, particularly improved CNN techniques, to classify and detect fraud in turmeric powder images with high accuracy. This study demonstrates that the integration of advanced CNN technology, such as gated pooling functions, can significantly enhance the accuracy and efficiency in assessing the quality and preventing fraud in turmeric powder.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

Article Engineering, Multidisciplinary

A noise robust convolutional neural network for image classification

Mohammad Momeny et al.

Summary: In this paper, a Noise-Robust Convolutional Neural Network (NR-CNN) is proposed to classify noisy images without preprocessing, by adding a noise map layer and an adaptive resize layer, and considering noise in different components of the network. The proposed NR-CNN improves the classification performance of noisy images and network training speed.

RESULTS IN ENGINEERING (2021)

Review Environmental Studies

Soil Protection in Floodplains-A Review

Mariam El Hourani et al.

Summary: This review assesses the type and extent of soil information used in research on floodplains and riparian zones, finding that soil classification is commonly used but often not fully described, with only single parameters mentioned. Physical, chemical, and biological soil properties are also mentioned in varying degrees in the research articles.
Article Soil Science

Classification of soil aggregates: A novel approach based on deep learning

Afshin Azizi et al.

SOIL & TILLAGE RESEARCH (2020)

Article Agronomy

Accurate classification of cherry fruit using deep CNN based on hybrid pooling approach

Mohammad Momeny et al.

POSTHARVEST BIOLOGY AND TECHNOLOGY (2020)

Article Chemistry, Analytical

Predicting soil texture using image analysis

Pedro Augusto de Oliveira Morais et al.

MICROCHEMICAL JOURNAL (2019)

Article Engineering, Multidisciplinary

Development of a novel machine vision procedure for rapid and non-contact measurement of soil moisture content

Fatemeh Rahimi-Ajdadi et al.

MEASUREMENT (2018)

Review Chemistry, Analytical

Machine Learning in Agriculture: A Review

Konstantinos G. Liakos et al.

SENSORS (2018)

Article Computer Science, Artificial Intelligence

Plant identification using deep neural networks via optimization of transfer learning parameters

Mostafa Mehdipour Ghazi et al.

NEUROCOMPUTING (2017)

Article Chemistry, Analytical

Deep Count: Fruit Counting Based on Deep Simulated Learning

Maryam Rahnemoonfar et al.

SENSORS (2017)

Article Multidisciplinary Sciences

Adequacy of laser diffraction for soil particle size analysis

Peter Fisher et al.

PLOS ONE (2017)

Proceedings Paper Engineering, Biomedical

Feature Extraction Using Deep Learning for Food Type Recognition

Muhammad Farooq et al.

BIOINFORMATICS AND BIOMEDICAL ENGINEERING, IWBBIO 2017, PT I (2017)

Article Agricultural Engineering

Plant species classification using deep convolutional neural network

Mads Dyrmann et al.

BIOSYSTEMS ENGINEERING (2016)

Article Chemistry, Analytical

DeepFruits: A Fruit Detection System Using Deep Neural Networks

Inkyu Sa et al.

SENSORS (2016)

Article Agriculture, Multidisciplinary

Analysis of texture-based features for predicting mechanical properties of horticultural products by laser light backscattering imaging

Kaveh Mollazade et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2013)

Article Soil Science

Simplified method for soil particle-size determination to accompany soil-quality analyses

TA Kettler et al.

SOIL SCIENCE SOCIETY OF AMERICA JOURNAL (2001)