1. “Identifying Growth Patterns in Arid-Zone Onion Crops (Allium Cepa) Using Digital Image Processing”
by David Duarte-Correa, Juvenal Rodríguez-Reséndiz, Germán Díaz-Flórez, Carlos Alberto Olvera-Olvera and José M. Álvarez-Alvarado
Technologies 2023, 11(3), 67; https://doi.org/10.3390/technologies11030067
Available online: https://www.mdpi.com/2227-7080/11/3/67
2. “Applied Deep Learning-Based Crop Yield Prediction: A Systematic Analysis of Current Developments and Potential Challenges”
by Khadija Meghraoui, Imane Sebari, Juergen Pilz, Kenza Ait El Kadi and Saloua Bensiali
Technologies 2024, 12(4), 43; https://doi.org/10.3390/technologies12040043
Available online: https://www.mdpi.com/2227-7080/12/4/43
3. “Deep Learning Approaches for Water Stress Forecasting in Arboriculture Using Time Series of Remote Sensing Images: Comparative Study between ConvLSTM and CNN-LSTM Models”
by Ismail Bounoua, Youssef Saidi, Reda Yaagoubi and Mourad Bouziani
Technologies 2024, 12(6), 77; https://doi.org/10.3390/technologies12060077
Available Online: https://www.mdpi.com/2227-7080/12/6/77
4. “Transformer-Based Water Stress Estimation Using Leaf Wilting Computed from Leaf Images and Unsupervised Domain Adaptation for Tomato Crops”
by Makoto Koike, Riku Onuma, Ryo Adachi and Hiroshi Mineno
Technologies 2024, 12(7), 94; https://doi.org/10.3390/technologies12070094
Available online: https://www.mdpi.com/2227-7080/12/7/94
5. “Smartphone-Based Citizen Science Tool for Plant Disease and Insect Pest Detection Using Artificial Intelligence”
by Panagiotis Christakakis, Garyfallia Papadopoulou, Georgios Mikos, Nikolaos Kalogiannidis, Dimosthenis Ioannidis, Dimitrios Tzovaras and Eleftheria Maria Pechlivani
Technologies 2024, 12(7), 101; https://doi.org/10.3390/technologies12070101
Available online: https://www.mdpi.com/2227-7080/12/7/101
6. “Change Detection for Forest Ecosystems Using Remote Sensing Images with Siamese Attention U-Net”
by Ashen Iranga Hewarathna, Luke Hamlin, Joseph Charles, Palanisamy Vigneshwaran, Romiyal George, Selvarajah Thuseethan, Chathrie Wimalasooriya and Bharanidharan Shanmugam
Technologies 2024, 12(9), 160; https://doi.org/10.3390/technologies12090160
Available online: https://www.mdpi.com/2227-7080/12/9/160
7. “Rice Leaf Disease Classification—A Comparative Approach Using Convolutional Neural Network (CNN), Cascading Autoencoder with Attention Residual U-Net (CAAR-U-Net), and MobileNet-V2 Architectures”
by Monoronjon Dutta, Md Rashedul Islam Sujan, Mayen Uddin Mojumdar, Narayan Ranjan Chakraborty, Ahmed Al Marouf, Jon G. Rokne and Reda Alhajj
Technologies 2024, 12(11), 214; https://doi.org/10.3390/technologies12110214
Available online: https://www.mdpi.com/2227-7080/12/11/214
