EDITOR'S CHOICE
A Cross-Domain Transfer Learning Framework for Robust Plant Disease Identification from Leaf Imagery
Kamal Kumar Srivastava, Choo Wou Onn, Vivek Kumar, Sameerchand Pudaruth, Suman Kumar Mishra
"SHARE YOUR KNOWLEDGE FOR A BETTER TOMORROW"
Knowledge has power, but it's much more powerful when it is shared
The Semarak International Journal of Machine Learning (SIJML) is a is a gold open-access, peer reviewed academic journal with the aim to provide an international platform for academic research by publishing original high-quality research and review articles. The journal scope includes but are not limited to data mining, artificial intelligence, natural language processing (NLP), neural networks, software engineering, bioinformatics and their applications in the areas of science and engineering.
Under evaluation by SCOPUS
Semarak International Journal of Machine Learning (SIJML) is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Malaysia, Saudi Arabia, Australia, India, Indonesia, Jordan, Oman, United States, Ghana, Mauritius, Japan, Canada
