Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6664687/
Code: https://github.com/mrlijun2017/Dual-CNN-RE
CNN-BLPred: a Convolutional neural network based predictor for β-Lactamases (BL) and their classes
Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751796/
Code: https://github.com/whiteclarence/CNN-BLPred
Design of deep convolutional networks for prediction of image rapid serial visual presentation events
Paper: https://www.ncbi.nlm.nih.gov/pubmed/29060296
Code: https://github.com/ZijingMao/ROICNN
A simple convolutional neural network for prediction of enhancer-promoter interactions with DNA sequence data
Paper: https://www.ncbi.nlm.nih.gov/pubmed/30649185
Code: https://github.com/zzUMN/Combine-CNN-Enhancer-and-Promoters
A novel attention-based hybrid CNN-RNN architecture for sEMG-based gesture recognition
Paper:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6207326/
Code: https://github.com/biopatrec/biopatrec
GRAM-CNN: a deep learning approach with local context for named entity recognition in biomedical text
Paper: https://www.ncbi.nlm.nih.gov/pubmed/29272325
Code: https://github.com/valdersoul/GRAM-CNN
Simple tricks of convolutional neural network architectures improve DNA-protein binding prediction
Paper: https://www.ncbi.nlm.nih.gov/pubmed/30351403
Code: https://github.com/zhanglabtools/DNADataAugmentation
EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation
Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5937476/
Code: https://github.com/shervinea/enzynet
Multi-timescale drowsiness characterization based on a video of a driver's face
Paper: https://www.telecom.ulg.ac.be/mts-drowsiness/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6165048/
Code: https://github.com/QMassoz/mts-drowsiness
CLoDSA: a tool for augmentation in classification, localization, detection, semantic segmentation and instance segmentation tasks
Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6567576/
Code: https://github.com/joheras/CLoDSA
Deep learning with convolutional neural networks for EEG decoding and visualization
Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5655781/
Code: https://github.com/robintibor/braindecode/
Code: https://github.com/TNTLFreiburg/braindecode
Classifying Oryza sativa accessions into Indica and Japonica using logistic regression model with phenotypic data
Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6842562/
Code: https://github.com/bongsongkim/logit.regression.rice
SNNRice6mA: A Deep Learning Method for Predicting DNA N6-Methyladenine Sites in Rice Genome
Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797597/
Code: https://github.com/yuht4/SNNRice6mA
Automatic estimation of heading date of paddy rice using deep learning
Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6626381/
Code: https://github.com/svdesai/heading-date-estimation
Distillation of crop models to learn plant physiology theories using machine learning
Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6541271/
Code: https://github.com/ky0on/simriw
Evaluating remote sensing datasets and machine learning algorithms for mapping plantations and successional forests in Phnom Kulen National Park of Cambodia
Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6814064/
Code: https://github.com/Jojo666/PKNP-Data
PlantCV v2: Image analysis software for high-throughput plant phenotyping
Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5713628/
Code: https://github.com/danforthcenter/plantcv-v2-paper
Crop Yield Prediction Using Deep Neural Networks
Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6540942/
Code: https://github.com/saeedkhaki92/Yield-Prediction-DNN
Using Deep Learning for Image-Based Plant Disease Detection
Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5032846/
Code: https://github.com/salathegroup/plantvillage_deeplearning_paper_analysis
Deep Plant Phenomics: A Deep Learning Platform for Complex Plant Phenotyping Tasks
Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5500639/
Code: https://github.com/p2irc/deepplantphenomics
DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning
Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6375952/
Code: https://github.com/AlexOlsen/DeepWeeds