In today’s digital era, the fresh fruit and vegetable industry faces numerous challenges such as efficient sorting and precise identification. To meet industry demands, we have successfully developed a customized algorithm with significant advantages in response to customer requirements, effectively solving problems related to image recognition and rapid application of fresh produce.

Enables image recognition for fresh produce, crafting tailored industry-specific solutions.

In traditional fresh produce recognition, reliance on manual labor has long been characterized by inefficiency and susceptibility to errors. Our customized algorithm, leveraging advanced deep learning techniques, enables precise identification of a wide range of fresh fruits and vegetables, encompassing common categories such as apples, bananas, oranges, strawberries, spinach, and cabbage—even extending to special varieties with visually similar appearances. Through holistic analysis of features including color, shape, texture, size, as well as indicators of freshness and defects, the algorithm achieves accurate classification and attribute determination for fresh produce.

Rapid Delivery

Upon receiving the requirement, our technical team swiftly completed the server deployment of the algorithm and migration of the embedded model. From requirement communication to the official deployment of the algorithm, the entire process took only one and a half months. By leveraging our algorithm, the enterprise achieved an intelligent upgrade of its production line, significantly improving production efficiency and gaining a competitive edge in the market.

High-precision recognition with continuous iterative optimization ensures sustained leadership in algorithm performance.