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Computer Vision in Deep Learning for the Detection of Cancer and its Treatment
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.
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