A Novel Convolutional-Recurrent Hybrid Network for Sunn Pest–Damaged Wheat Grain Detection

Characterization and virulence of entomopathogenic fungi from sunn pests in Turkey

(2021) Esra Gül et al.   JOURNAL OF ASIA-PACIFIC ENTOMOLOGY

A CNN-based novel solution for determining the survival status of heart failure patients with clinical record data: numeric to image

(2021) Muhammet Fatih Aslan et al.   Biomedical Signal Processing and Control

A CNN-SVM study based on selected deep features for grapevine leaves classification

(2021) Murat Koklu et al.   MEASUREMENT

Automated defect inspection system for metal surfaces based on deep learning and data augmentation

(2020) Jong Pil Yun et al.   JOURNAL OF MANUFACTURING SYSTEMS

An optimized dense convolutional neural network model for disease recognition and classification in corn leaf

(2020) Abdul Waheed et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

CNN-based transfer learning–BiLSTM network: A novel approach for COVID-19 infection detection

(2020) Muhammet Fatih Aslan et al.   APPLIED SOFT COMPUTING

Identification of impurity in wheat mass based on video processing using artificial neural network and PSO algorithm

(2020) Saeed AgaAzizi et al.   JOURNAL OF FOOD PROCESSING AND PRESERVATION

Identification of wheat kernels by fusion of RGB, SWIR, VNIR samples over feature and image domain

(2019) Kemal Özkan et al.   JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE

Application of Deep Learning in Neuroradiology: Brain Haemorrhage Classification Using Transfer Learning

(2019) Awwal Muhammad Dawud et al.   Computational Intelligence and Neuroscience

Crop pest classification based on deep convolutional neural network and transfer learning

(2019) K. Thenmozhi et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Detection of sunn pest‐damaged wheat grains using artificial bee colony optimization‐based artificial intelligence techniques

(2019) Kadir Sabanci   JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE

Transfer learning for the classification of sugar beet and volunteer potato under field conditions

(2018) Hyun K. Suh et al.   BIOSYSTEMS ENGINEERING

A review of research on Sunn Pest { Eurygaster integriceps Puton (Hemiptera: Scutelleridae)} management published 2004–2016

(2018) Agrin Davari et al.   JOURNAL OF ASIA-PACIFIC ENTOMOLOGY

Detection of sunn pest-damaged wheat samples using visible/near-infrared spectroscopy based on pattern recognition

(2018) Zahra Basati et al.   SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY

A review of research on Sunn Pest { Eurygaster integriceps Puton (Hemiptera: Scutelleridae)} management published 2004–2016

(2018) Agrin Davari et al.   JOURNAL OF ASIA-PACIFIC ENTOMOLOGY

Rapid determination of total protein and wet gluten in commercial wheat flour using siSVR-NIR

(2017) Jia Chen et al.   FOOD CHEMISTRY

Wheat grain classification by using dense SIFT features with SVM classifier

(2016) Murat Olgun et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Computer vision-based method for classification of wheat grains using artificial neural network

(2016) Kadir Sabanci et al.   JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE

Deep learning

(2015) Yann LeCun et al.   NATURE

Image acquisition techniques for assessment of legume quality

(2015) Shveta Mahajan et al.   TRENDS IN FOOD SCIENCE & TECHNOLOGY

The development of a hyperspectral imaging method for the detection of Fusarium-damaged, yellow berry and vitreous Italian durum wheat kernels

(2013) Silvia Serranti et al.   BIOSYSTEMS ENGINEERING

Characterization of a prolyl endoprotease from Eurygaster integriceps puton (Sunn pest) infested wheat

(2010) Charles Darkoh et al.   ARCHIVES OF INSECT BIOCHEMISTRY AND PHYSIOLOGY

Detection of Fusarium damaged kernels in Canada Western Red Spring wheat using visible/near-infrared hyperspectral imaging and principal component analysis

(2010) Muhammad A. Shahin et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Detection of insect-damaged wheat kernels using near-infrared hyperspectral imaging

(2009) C.B. Singh et al.   JOURNAL OF STORED PRODUCTS RESEARCH