Demystifying Convolutional Neural Networks using GradCam - WebSystemer.no

Convolutional Neural Networks(CNNs) and other deep learning networks have enabled unprecedented breakthroughs in a variety of computer vision tasks from image classification to object detection, semantic segmentation, image captioning and more recently visual question answering. While these networks enable superior performance, their lack of decomposability into intuitive and understandable components makes them hard to interpret. Consequently, when today's intelligent systems fail, they fail spectacularly disgracefully without warning or explanation, leaving a user staring at an incoherent output, wondering why. Interpretability of Deep Learning models matters to build trust and move towards their successful integration in our daily lives. To achieve this goal the model transparency is useful to explain why they predict what they predict.