QCNN for Object Detection and Classification

In order to efficiently discover and classify objects on the COCO and Pascal voc dataset, this investigation proposes a Quantum Convolutional Neural Network (QCNN) coupled with Grover's Algorithm. The suggested method seeks to improve the precision and computational effectiveness of object recognition by utilizing quantum feature extraction and quantum search techniques. We outline the experimental outcomes, quantum circuit implementation, and mathematical underpinnings of Qiskit.