MobiRes-Net: A Hybrid Deep Learning Model for Detecting and Classifying Olive Leaf Diseases

Different stages of disease detection in squash plant based on machine learning

(2022) R Ganesh Babu et al.   JOURNAL OF BIOSCIENCES

Recognition of Leaf Disease Using Hybrid Convolutional Neural Network by Applying Feature Reduction

(2022) Prabhjot Kaur et al.   SENSORS

Classification and yield prediction in smart agriculture system using IoT

(2022) Akanksha Gupta et al.   Journal of Ambient Intelligence and Humanized Computing

Optimized Deep Learning Algorithms for Tomato Leaf Disease Detection with Hardware Deployment

(2022) Hesham Tarek et al.   Electronics

Autonomous flying IoT: A synergy of machine learning, digital elevation, and 3D structure change detection

(2022) Faris A. Almalki et al.   COMPUTER COMMUNICATIONS

Novel Enhanced-Grey Wolf Optimization hybrid machine learning technique for biomedical data computation

(2022) Chinmay Chakraborty et al.   COMPUTERS & ELECTRICAL ENGINEERING

Design and Evaluation of a Hybrid Technique for Detecting Sunflower Leaf Disease Using Deep Learning Approach

(2022) Arun Malik et al.   JOURNAL OF FOOD QUALITY

A novel sample and feature dependent ensemble approach for Parkinson’s disease detection

(2022) Liaqat Ali et al.   NEURAL COMPUTING & APPLICATIONS

Scarcity-aware spam detection technique for big data ecosystem

(2022) Woo Hyun Park et al.   PATTERN RECOGNITION LETTERS

Modifying Hata-Davidson Propagation Model for Remote Sensing in Complex Environments Using a Multifactional Drone

(2022) Faris A. Almalki et al.   SENSORS

Optimal Deep Learning Model for Olive Disease Diagnosis Based on an Adaptive Genetic Algorithm

(2022) Hamoud Alshammari et al.   WIRELESS COMMUNICATIONS & MOBILE COMPUTING

Extraction of Olive Crown Based on UAV Visible Images and the U2-Net Deep Learning Model

(2022) Zhangxi Ye et al.   Remote Sensing

Banana Plant Disease Classification Using Hybrid Convolutional Neural Network

(2022) K. Lakshmi Narayanan et al.   Computational Intelligence and Neuroscience

Detecting High-Risk Factors and Early Diagnosis of Diabetes Using Machine Learning Methods

(2022) Zahid Ullah et al.   Computational Intelligence and Neuroscience

IoE based framework for smart agriculture

(2021) Hitesh Mohapatra et al.   Journal of Ambient Intelligence and Humanized Computing

Disease detection in tomato leaves via CNN with lightweight architectures implemented in Raspberry Pi 4

(2021) Victor Gonzalez-Huitron et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Application of deep convolutional neural networks for the detection of anthracnose in olives using VIS/NIR hyperspectral images

(2021) Antonio Fazari et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

COVID ‐19 diagnosis system by deep learning approaches

(2021) Hemanta Kumar Bhuyan et al.   EXPERT SYSTEMS

Intrusion Detection in Industrial Internet of Things Network-Based on Deep Learning Model with Rule-Based Feature Selection

(2021) Joseph Bamidele Awotunde et al.   WIRELESS COMMUNICATIONS & MOBILE COMPUTING

PlantDiseaseNet: convolutional neural network ensemble for plant disease and pest detection

(2021) Muammer Turkoglu et al.   Signal Image and Video Processing

A Low-Cost Platform for Environmental Smart Farming Monitoring System Based on IoT and UAVs

(2021) Faris A. Almalki et al.   Sustainability

A cucumber leaf disease severity classification method based on the fusion of DeepLabV3+ and U-Net

(2021) Chunshan Wang et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Classification of olive leaf diseases using deep convolutional neural networks

(2020) Sinan Uğuz et al.   NEURAL COMPUTING & APPLICATIONS

Performance of deep learning vs machine learning in plant leaf disease detection

(2020) R. Sujatha et al.   MICROPROCESSORS AND MICROSYSTEMS

Identification of plant leaf diseases using a nine-layer deep convolutional neural network

(2019) Geetharamani G. et al.   COMPUTERS & ELECTRICAL ENGINEERING

Deep learning models for plant disease detection and diagnosis

(2018) Konstantinos P. Ferentinos   COMPUTERS AND ELECTRONICS IN AGRICULTURE

X-FIDO: An Effective Application for Detecting Olive Quick Decline Syndrome with Deep Learning and Data Fusion

(2017) Albert C. Cruz et al.   Frontiers in Plant Science