The paper surveys a vegetable recognition system and recipe generation based on the latest architecture of YOLOv8 in deep learning for enhanced object detection. The model is trained with a robust set of images about vegetables, so it can distinguish wide range of vegetables. Thus, the output information can be used to feedback into the system with suggestions for recipes according to the vegetables to provide the users with personalized suggestions to explore new culinary possibilities in a highly efficient manner. It is designed to automate the cooking process by automatically linking the detected ingredients to relevant recipes, thereby enhancing ease and speed of meal preparation. State-of-the-art advancements in deep learning ensure that there is an easy and efficient approach to automating ingredient recognition and culinary exploration, thereby making this project exemplar at the crossroads of artificial intelligence and culinary innovation.