How ConvNets found a way to survive the Transformers invasion in computer vision

Traditionally, Convolutional Neural Networks (CNN) have been the preferred choice for computer vision tasks. CNNs, composed of layers of artificial neurons, calculate the weighted sum of the inputs to give output in the form of activation values. In the case of computer vision applications, CNNs accept pixel values to output various visual features. Indubitably, the invention of AlexNet was the apogee of the CNN movement. AlexNet has become the leading CNN-based architecture for object detection tasks in the computer vision field.