An advanced deep learning models-based plant disease detection: A review of recent research

M Shoaib, B Shah, S Ei-Sappagh, A Ali… - Frontiers in Plant …, 2023 - frontiersin.org
Plants play a crucial role in supplying food globally. Various environmental factors lead to
plant diseases which results in significant production losses. However, manual detection of …

A survey of deep convolutional neural networks applied for prediction of plant leaf diseases

VS Dhaka, SV Meena, G Rani, D Sinwar, MF Ijaz… - Sensors, 2021 - mdpi.com
In the modern era, deep learning techniques have emerged as powerful tools in image
recognition. Convolutional Neural Networks, one of the deep learning tools, have attained …

[PDF][PDF] 卷积神经网络研究综述

周飞燕, 金林鹏, 董军 - 计算机学报, 2017 - cjc.ict.ac.cn
摘要作为一个十余年来快速发展的崭新领域, 深度学习受到了越来越多研究者的关注,
它在特征提取和模型拟合上都有着相较于浅层模型显然的优势. 深度学习善于从原始输入数据中 …

Deep learning: Applications, architectures, models, tools, and frameworks: A comprehensive survey

M Gheisari, F Ebrahimzadeh, M Rahimi… - CAAI Transactions …, 2023 - Wiley Online Library
Deep Learning (DL) is a subfield of machine learning that significantly impacts extracting
new knowledge. By using DL, the extraction of advanced data representations and …

Machine learning and deep learning frameworks and libraries for large-scale data mining: a survey

G Nguyen, S Dlugolinsky, M Bobák, V Tran… - Artificial Intelligence …, 2019 - Springer
The combined impact of new computing resources and techniques with an increasing
avalanche of large datasets, is transforming many research areas and may lead to …

Deep learning in agriculture: A survey

A Kamilaris, FX Prenafeta-Boldú - Computers and electronics in agriculture, 2018 - Elsevier
Deep learning constitutes a recent, modern technique for image processing and data
analysis, with promising results and large potential. As deep learning has been successfully …

Convolutional neural networks in detection of plant leaf diseases: A review

B Tugrul, E Elfatimi, R Eryigit - Agriculture, 2022 - mdpi.com
Rapid improvements in deep learning (DL) techniques have made it possible to detect and
recognize objects from images. DL approaches have recently entered various agricultural …

Deep learning in mining biological data

M Mahmud, MS Kaiser, TM McGinnity, A Hussain - Cognitive computation, 2021 - Springer
Recent technological advancements in data acquisition tools allowed life scientists to
acquire multimodal data from different biological application domains. Categorized in three …

[HTML][HTML] Deep learning in medical ultrasound analysis: a review

S Liu, Y Wang, X Yang, B Lei, L Liu, SX Li, D Ni… - Engineering, 2019 - Elsevier
Ultrasound (US) has become one of the most commonly performed imaging modalities in
clinical practice. It is a rapidly evolving technology with certain advantages and with unique …

Deep learning for IoT big data and streaming analytics: A survey

M Mohammadi, A Al-Fuqaha, S Sorour… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
In the era of the Internet of Things (IoT), an enormous amount of sensing devices collect
and/or generate various sensory data over time for a wide range of fields and applications …