Nowadays agriculture field is one of the important fields that plays a crucial role in the economics of countries. Therefore the study of diseases related to plants, fruits and vegetables is of great importance in improving the quality of products. Thus in this paper we focuses on the detection of leaf diseases using advanced deep learning techniques, specifically convolutional neural networks (CNN), Inception V3, and YOLOv8 architectures, this study focuses on the identification and classification of common wheat leaf diseases such as Septoria and Stripe rust, as well as distinguishing healthy leaves. The results demonstrate significant improvements in disease detection accuracy, offering a promising tool for farmers and agronomists.