IJIRCSTJournal International Journal of Innovative Research in Computer Science and Technology I S Volume 14 Issue 2 Computer Science English March - April 2026 N N Y 2026 04 07 Computer Sciences Automated Plant Disease Detection and Recognition Using Convolutional Neural Network English Y 52 59 Ayesha Rehan English Y Avanish Verma English N Chitransh Nigam English N https://doi.org/10.55524/ijircst.2026.14.2.7 Sustainable Agriculture has reduced environmental harms, aids and expands natural resources for productive purpose. It allows the production of crops to ensures global food security. Plant Diseases leading to considerable crop losses and economic challenges for farmers. In the era of Modern technology there is a need of fast and accurate detection is essential for effective intervention and management. Modern innovation and research developments in machine learning and deep learning enabled automated plant disease detection that are providing fast scalable, and highly accurate solutions. While previous models are implemented for single type plant to get higher accuracy and therefore, they need high-resolution images. Convolutional Neural Network provide excellent performance in classifying and identifying diseases from datasets of plant leaves images with low resolutions. The usage of pre-trained models and a focus on the fine tuning of the hyperparameters leads the highest accuracy in detecting plant disease. However, there is need of strategy, adaptability, and robustness to achieve goals. English Plant Disease Detection, Convolutional Neural Network, Accuracy https://ijircst.org/abstract.php?article_id=1454