Project Architecture Overview Creating an image recognition application involves three primary stages: collecting a dataset, training a convolusional neural network, and deploying the model through a web interface. Each phase is outlined with concrete implementation steps. 1. Data Acquisition Machin...
The task of distinguishing cats from dogs originates from a beginner-level Kaggle competition titled Dogs vs Cats. To gain deeper insights into Convolutional Neural Networks (CNNs), several classic models like LeNet, AlexNet, and ResNet were implemented using PyTorch. This exploration investigates h...
RDNet is an enhanced version of the DenseNet architecture, designed to improve performance and computational efficiency through key modifications. The model emphasizes concatenation operations over additive shortcuts, expands intermediate channel dimensions by adjusting the expansion ratio independe...