Agriculture plays a paramount role in the economic growth of countries such as India, where demand for food supplies is high. Extreme weather and climate changes can increase the risk of plants being attacked by infectious diseases. Fungi, viruses, or bacteria can create a dangerous environment for plants. Plants are an essential part of our world, providing food and other products that many industries rely upon. With the diseases they face, it's important to identify and treat them as early as possible. Conventional plant identification methods relied on experts in the field and were time-consuming or impractical. We experimented with deep learning-based approaches for the purpose of the disease detection and classification, especially AlexNet, which is a leading architecture for object-detection tasks. VGG-16 also presents excellent performance when detecting objects. ResNet-50 has even better performance in this task and it's 50 layers deep. This paper aims for the disease detection on samples of Sunflowers.