<ul><li>Through this journey, a comparative study was conducted on ResNet-50, ResNet-34, and Inception-v3 architectures to solve the problem of distinguishing between eight weed species from over 17,000 images.</li><li>The selected weed species are local to pastoral grasslands in Queensland and include Chinee apple, Snakeweed, Lantana, Prickly acacia, Siam weed, Parthenium, Rubber vine, and Parkinsonia.</li><li>Pretrained Inception-v3 achieved the highest validation accuracy (92%) and the lowest validation loss (~0.2), indicating superior generalization.</li><li>A detailed classification report revealed key findings about the model performance.</li></ul>

Detecting Plant Weeds with CNN Models: A Deep Dive into ResNet and Inception-v3

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