Improving Deep Learning Classifiers Performance via Preprocessing and Class Imbalance Approaches in a Plant Disease Detection Pipeline

Deep Learning in Controlled Environment Agriculture: A Review of Recent Advancements, Challenges and Prospects

(2022) Mike O. Ojo et al.   SENSORS

Construction of Apple Leaf Diseases Identification Networks Based on Xception Fused by SE Module

(2021) Xiaofei Chao et al.   Applied Sciences-Basel

Evaluating the Single-Shot MultiBox Detector and YOLO Deep Learning Models for the Detection of Tomatoes in a Greenhouse

(2021) Sandro Augusto Magalhães et al.   SENSORS

Image augmentation to improve construction resource detection using generative adversarial networks, cut-and-paste, and image transformation techniques

(2020) Seongdeok Bang et al.   AUTOMATION IN CONSTRUCTION

Appropriateness of performance indices for imbalanced data classification: An analysis

(2020) Sankha Subhra Mullick et al.   PATTERN RECOGNITION

Imbalance Problems in Object Detection: A Review

(2020) Kemal Oksuz et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

LeafGAN: An Effective Data Augmentation Method for Practical Plant Disease Diagnosis

(2020) Quan Huu Cap et al.   IEEE Transactions on Automation Science and Engineering

Detection of Apple Lesions in Orchards Based on Deep Learning Methods of CycleGAN and YOLOV3-Dense

(2019) Yunong Tian et al.   Journal of Sensors

A low shot learning method for tea leaf’s disease identification

(2019) Gensheng Hu et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Accurate prediction of soluble solid content of apples from multiple geographical regions by combining deep learning with spectral fingerprint features

(2019) Yuhao Bai et al.   POSTHARVEST BIOLOGY AND TECHNOLOGY

Deep learning models for plant disease detection and diagnosis

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

On the Reconstruction of Face Images from Deep Face Templates

(2018) Guangcan Mai et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

A systematic study of the class imbalance problem in convolutional neural networks

(2018) Mateusz Buda et al.   NEURAL NETWORKS

Deep Learning for Plant Stress Phenotyping: Trends and Future Perspectives

(2018) Asheesh Kumar Singh et al.   TRENDS IN PLANT SCIENCE

Ralstonia solanacearum Differentially Colonizes Roots of Resistant and Susceptible Tomato Plants

(2017) Denise Caldwell et al.   PHYTOPATHOLOGY

Using Deep Learning for Image-Based Plant Disease Detection

(2016) Sharada P. Mohanty et al.   Frontiers in Plant Science

Automatic grading of Bi-colored apples by multispectral machine vision

(2010) Devrim Unay et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE