Deep Learning Approaches For Object Recognition In Plant Diseases A Review

Author : Zimo Zhou ,Yue Zhang, Zhaohui Gu,Simon X. Yang
Publisher : OAE Publishing Inc.
Page : 24 pages
File Size : 42,5 Mb
Release : 2023-10-28
Category : Computers
ISBN : 8210379456XXX

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Deep learning approaches for object recognition in plant diseases: a review by Zimo Zhou ,Yue Zhang, Zhaohui Gu,Simon X. Yang Pdf

Plant diseases pose a significant threat to the economic viability of agriculture and the normal functioning of trees in forests. Accurate detection and identification of plant diseases are crucial for smart agricultural and forestry management. Artificial intelligence has been successfully applied to agriculture in recent years. Many intelligent object recognition algorithms, specifically deep learning approaches, have been proposed to identify diseases in plant images. The goal is to reduce labor and improve detection efficiency. This article reviews the application of object detection methods for detecting common plant diseases, such as tomato, citrus, maize, and pine trees. It introduces various object detection models, ranging from basic to modern and sophisticated networks, and compares the innovative aspects and drawbacks of commonly used neural network models. Furthermore, the article discusses current challenges in plant disease detection and object detection methods and suggests promising directions for future work in learning-based plant disease detection systems.

Author : Jucheng Yang,Yalin Wu,Alvaro Fuentes,Sook Yoon,Tonghai Liu
Publisher : Frontiers Media SA
Page : 350 pages
File Size : 51,9 Mb
Release : 2024-06-06
Category : Science
ISBN : 9782832550090

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Advanced AI Methods for Plant Disease and Pest Recognition by Jucheng Yang,Yalin Wu,Alvaro Fuentes,Sook Yoon,Tonghai Liu Pdf

Plant diseases and pests cause significant losses to farmers and threaten food security worldwide. Monitoring the growing conditions of crops and detecting plant diseases is critical for sustainable agriculture. Traditionally, crop inspection has been carried out by people with expert knowledge in the field. However, regarding any activity carried out by humans, this activity is prone to errors, leading to possible incorrect decisions. Innovation is, therefore, an essential fact of modern agriculture. In this context, deep learning has played a key role in solving complicated applications with increasing accuracy over time, and recent interest in this type of technology has prompted its potential application to address complex problems in agriculture, such as plant disease and pest recognition. Although substantial progress has been made in the area, several challenges still remain, especially those that limit systems to operate in real-world scenarios.

Author : Jacques Blanc-Talon,Patrice Delmas,Wilfried Philips,Dan Popescu,Paul Scheunders
Publisher : Springer Nature
Page : 576 pages
File Size : 48,5 Mb
Release : 2020-02-05
Category : Computers
ISBN : 9783030406059

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Advanced Concepts for Intelligent Vision Systems by Jacques Blanc-Talon,Patrice Delmas,Wilfried Philips,Dan Popescu,Paul Scheunders Pdf

This book constitutes the proceedings of the 20th INternational Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2020, held in Auckland, New Zealand, in February 2020. The 48 papers presented in this volume were carefully reviewed and selected from a total of 78 submissions. They were organized in topical sections named: deep learning; biomedical image analysis; biometrics and identification; image analysis; image restauration, compression and watermarking; tracking, and mapping and scene analysis.

Author : Rujing Wang,Peng Chen,Po Yang
Publisher : Frontiers Media SA
Page : 244 pages
File Size : 41,6 Mb
Release : 2023-04-05
Category : Science
ISBN : 9782832517741

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Deep learning in crop diseases and insect pests by Rujing Wang,Peng Chen,Po Yang Pdf

Author : Boris Kryzhanovsky,Witali Dunin-Barkowski,Vladimir Redko,Yury Tiumentsev
Publisher : Springer
Page : 344 pages
File Size : 42,6 Mb
Release : 2018-10-07
Category : Computers
ISBN : 3030013278

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Advances in Neural Computation, Machine Learning, and Cognitive Research II by Boris Kryzhanovsky,Witali Dunin-Barkowski,Vladimir Redko,Yury Tiumentsev Pdf

This book describes new theories and applications of artificial neural networks, with a special focus on addressing problems in neuroscience, biology and biophysics and cognitive research. It covers a wide range of methods and technologies, including deep neural networks, large-scale neural models, brain–computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more. The book includes both selected and invited papers presented at the XX International Conference on Neuroinformatics, held in Moscow, Russia on October 8–12, 2018.

Author : S Poonkuntran,Rajesh Kumar Dhanraj,Balamurugan Balusamy
Publisher : CRC Press
Page : 276 pages
File Size : 52,5 Mb
Release : 2022-11-01
Category : Computers
ISBN : 9781000686746

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Object Detection with Deep Learning Models by S Poonkuntran,Rajesh Kumar Dhanraj,Balamurugan Balusamy Pdf

Object Detection with Deep Learning Models discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in deep learning, computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks. Features: A structured overview of deep learning in object detection A diversified collection of applications of object detection using deep neural networks Emphasize agriculture and remote sensing domains Exclusive discussion on moving object detection

Author : Ben Othman Soufiene,Chinmay Chakraborty
Publisher : CRC Press
Page : 270 pages
File Size : 42,8 Mb
Release : 2023-12-01
Category : Technology & Engineering
ISBN : 9781003805670

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Machine Learning and Deep Learning Techniques for Medical Image Recognition by Ben Othman Soufiene,Chinmay Chakraborty Pdf

Machine Learning and Deep Learning Techniques for Medical Image Recognition comprehensively reviews deep learning-based algorithms in medical image analysis problems including medical image processing. It includes a detailed review of deep learning approaches for semantic object detection and segmentation in medical image computing and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks with the theory and varied selection of techniques for semantic segmentation using deep learning principles in medical imaging supported by practical examples. Features: Offers important key aspects in the development and implementation of machine learning and deep learning approaches toward developing prediction tools and models and improving medical diagnosis Teaches how machine learning and deep learning algorithms are applied to a broad range of application areas, including chest X-ray, breast computer-aided detection, lung and chest, microscopy, and pathology Covers common research problems in medical image analysis and their challenges Focuses on aspects of deep learning and machine learning for combating COVID-19 Includes pertinent case studies This book is aimed at researchers and graduate students in computer engineering, artificial intelligence and machine learning, and biomedical imaging.

Author : Muhammad Fazal Ijaz,Marcin Wozniak
Publisher : Frontiers Media SA
Page : 379 pages
File Size : 52,6 Mb
Release : 2024-02-19
Category : Science
ISBN : 9782832544952

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Recent Advances in Big Data, Machine, and Deep Learning for Precision Agriculture by Muhammad Fazal Ijaz,Marcin Wozniak Pdf

Author : Le Lu,Xiaosong Wang,Gustavo Carneiro,Lin Yang
Publisher : Springer Nature
Page : 461 pages
File Size : 50,6 Mb
Release : 2019-09-19
Category : Computers
ISBN : 9783030139698

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Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics by Le Lu,Xiaosong Wang,Gustavo Carneiro,Lin Yang Pdf

This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construction and mining of large-scale radiology databases. It particularly focuses on the application of convolutional neural networks, and on recurrent neural networks like LSTM, using numerous practical examples to complement the theory. The book’s chief features are as follows: It highlights how deep neural networks can be used to address new questions and protocols, and to tackle current challenges in medical image computing; presents a comprehensive review of the latest research and literature; and describes a range of different methods that employ deep learning for object or landmark detection tasks in 2D and 3D medical imaging. In addition, the book examines a broad selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to text and image deep embedding for a large-scale chest x-ray image database; and discusses how deep learning relational graphs can be used to organize a sizable collection of radiology findings from real clinical practice, allowing semantic similarity-based retrieval. The intended reader of this edited book is a professional engineer, scientist or a graduate student who is able to comprehend general concepts of image processing, computer vision and medical image analysis. They can apply computer science and mathematical principles into problem solving practices. It may be necessary to have a certain level of familiarity with a number of more advanced subjects: image formation and enhancement, image understanding, visual recognition in medical applications, statistical learning, deep neural networks, structured prediction and image segmentation.

Author : Rujing Wang,Lin Jiao,Kang Liu
Publisher : Springer Nature
Page : 140 pages
File Size : 52,5 Mb
Release : 2023-09-20
Category : Computers
ISBN : 9789819949731

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Deep Learning for Agricultural Visual Perception by Rujing Wang,Lin Jiao,Kang Liu Pdf

This monograph provides a detailed and systematic introduction to the application of deep learning technology in the intelligent monitoring of crop diseases and pests. Taking 24 types of crop pests, wheat aphids, and wheat diseases with complex backgrounds as examples, a large-scale crop pest and disease dataset was constructed to provide necessary data support for the deep learning module. Various schemes for identifying and detecting large-scale crop diseases and pests based on deep convolutional neural network technology have also been proposed. This book can be used as a reference for teachers and students majoring in agriculture, computer science, artificial intelligence, intelligent science and technology, and other related fields in higher education institutions. It can also be used as a reference book for researchers in fields such as image processing technology, intelligent manufacturing, and high-tech applications.

Author : Le Lu,Yefeng Zheng,Gustavo Carneiro,Lin Yang
Publisher : Springer
Page : 326 pages
File Size : 55,7 Mb
Release : 2017-07-12
Category : Computers
ISBN : 9783319429991

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Deep Learning and Convolutional Neural Networks for Medical Image Computing by Le Lu,Yefeng Zheng,Gustavo Carneiro,Lin Yang Pdf

This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.

Author : José Dias Pereira,Liangliang Yang ,Jian Lian,Dengchao Feng
Publisher : Frontiers Media SA
Page : 245 pages
File Size : 41,5 Mb
Release : 2024-05-10
Category : Science
ISBN : 9782832548929

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IoT, UAV, BCI Empowered Deep Learning models in Precision Agriculture by José Dias Pereira,Liangliang Yang ,Jian Lian,Dengchao Feng Pdf

Machine vision applications in precision agriculture have attracted a great deal of attention. They focus on monitoring, protection, and management of various plant populations. These applications have shown potential value in reforming crucial components of plant production, including fine-grained ripeness recognition of all kinds of plants and detecting and classifying weeds, seeds, and pests for crop health, quality, and quantity enhancement. In recent decades, the extensive achievements of deep learning techniques have shown significant opportunities for almost all fields. Accordingly, many deep learning models have been presented for different types of images and have achieved promising outcomes. The deep learning-based approaches can contribute to gaining insights into the plants' inherent characteristics and the surrounding environmental elements. This research topic's primary value is providing a platform for deep learning-based applications for precision agriculture. These applications can be fairly evaluated and compared with each other. Accordingly, more effective and efficient detection and classification approaches for precision agriculture can be developed or optimized.

Author : Mohammad Shorif Uddin,Jagdish Chand Bansal
Publisher : Springer Nature
Page : 269 pages
File Size : 41,7 Mb
Release : 2022-03-13
Category : Technology & Engineering
ISBN : 9789811699917

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Computer Vision and Machine Learning in Agriculture, Volume 2 by Mohammad Shorif Uddin,Jagdish Chand Bansal Pdf

This book is as an extension of previous book “Computer Vision and Machine Learning in Agriculture” for academicians, researchers, and professionals interested in solving the problems of agricultural plants and products for boosting production by rendering the advanced machine learning including deep learning tools and techniques to computer vision algorithms. The book contains 15 chapters. The first three chapters are devoted to crops harvesting, weed, and multi-class crops detection with the help of robots and UAVs through machine learning and deep learning algorithms for smart agriculture. Next, two chapters describe agricultural data retrievals and data collections. Chapters 6, 7, 8 and 9 focuses on yield estimation, crop maturity detection, agri-food product quality assessment, and medicinal plant recognition, respectively. The remaining six chapters concentrates on optimized disease recognition through computer vision-based machine and deep learning strategies.

Author : Sanjiban Sekhar Roy,Ching-Hsien Hsu,Venkateshwara Kagita
Publisher : Springer Nature
Page : 218 pages
File Size : 53,6 Mb
Release : 2023-07-08
Category : Technology & Engineering
ISBN : 9789819937844

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Deep Learning Applications in Image Analysis by Sanjiban Sekhar Roy,Ching-Hsien Hsu,Venkateshwara Kagita Pdf

This book provides state-of-the-art coverage of deep learning applications in image analysis. The book demonstrates various deep learning algorithms that can offer practical solutions for various image-related problems; also how these algorithms are used by scientists and scholars in industry and academia. This includes autoencoder and deep convolutional generative adversarial network in improving classification performance of Bangla handwritten characters, dealing with deep learning-based approaches using feature selection methods for automatic diagnosis of covid-19 disease from x-ray images, imbalance image data sets of classification, image captioning using deep transfer learning, developing a vehicle over speed detection system, creating an intelligent system for video-based proximity analysis, building a melanoma cancer detection system using deep learning, plant diseases classification using AlexNet, dealing with hyperspectral images using deep learning, chest x-ray image classification of pneumonia disease using efficient net and inceptionv3. The book also addresses the difficulty of implementing deep learning in terms of computation time and the complexity of reasoning and modelling different types of data where information is currently encoded. Each chapter has the application of various new or existing deep learning models such as Deep Neural Network (DNN) and Deep Convolutional Neural Networks (DCNN). The detailed utilization of deep learning packages that are available in MATLAB, Python and R programming environments have also been discussed, therefore, the readers will get to know about the practical implementation of deep learning as well. The content of this book is presented in a simple and lucid style for professionals, nonprofessionals, scientists, and students interested in the research area of deep learning applications in image analysis.

Author : Azeddine Elhassouny,Florentin Smarandache
Publisher : Infinite Study
Page : 4 pages
File Size : 52,6 Mb
Release : 2024-06-29
Category : Mathematics
ISBN : 8210379456XXX

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Smart mobile application to recognize tomato leaf diseases using Convolutional Neural Networks by Azeddine Elhassouny,Florentin Smarandache Pdf

The automatic identification and diagnosis of tomato leaves diseases are highly desired in field of agriculture information. Recently Deep Convolutional Neural networks (CNN) has made tremendous advances in many fields, close to computer vision such as classification, object detection, segmentation, achieving better accuracy than human-level perception. In spite of its tremendous advances in computer vision tasks, CNN face many challenges, such as computational burden and energy, to be used in mobile phone and embedded systems.