ABSTRACT

Computer vision (CV) is an effective mechanism that helps the computer to see pictorial stimuli from pointing out the edges to having a comprehensive understanding of the complete scenario. In this saga, Deep Learning (DL) has evolved as a crucial part of CV to process data exploiting multi-layered complex structures or layers made of multiple nonlinear alterations. This particular research shows the implementation of DL in the proper diagnosis of cancer and seeking a suitable solution to the disease. DL is an integral part of CV considering a multimodal discriminative model to conduct a diagnosis of diseases, clinical predictions, prognostics, and a combination of such activities. The study upholds the relevance of SSD in having single-shot images with high-resolution pixels to have the images to identify and diagnose the disease. The mechanism leads to early detection of cancer and if the disease gets detected earlier, it can seek a formidable solution, though there are challenges like an alignment of hardware with the CV software, and lack of training of the staff, still DL has the potentiality to create a significant impact on cancer treatment

Keywords: - Computer Vision (CV), Deep Learning (DL), Single Shot Detector (SSD), Cancer Detection Algorithms