1) The document proposes a system to identify malaria parasites in cells using object detection with faster R-CNN, which can identify different parasite types and stages more accurately and faster than previous methods. 2) Malaria is caused by plasmodium parasites transmitted by mosquitos. The proposed system uses image processing and faster R-CNN to detect parasites in microscopic images of blood cells to help practitioners diagnose malaria faster and reduce misdiagnoses. 3) Faster R-CNN is trained on labeled images of infected and uninfected cells. It can detect parasite types and stages with 98% accuracy and bounding boxes highlighting the detections. This helps improve malaria diagnosis over traditional microscopic examination.