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marvin
2026-05-01 02:10:03 +02:00
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commit d801d6d59d
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cnn_website/src/Bird_CNN.css
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@@ -63,7 +63,7 @@ a:hover {
flex-wrap: wrap; flex-wrap: wrap;
overflow: hidden; overflow: hidden;
border-radius: 12px; border-radius: 12px;
margin: 180px 50px 0px 50px; margin: 180px 50px 50px 50px;
} }
.image-box { .image-box {
cnn_website/src/Bird_CNN.jsx
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@@ -123,7 +123,7 @@ function Bird_CNN() {
<div style={{ display: "inline" }}> <div style={{ display: "inline" }}>
<span>The model used for classification is a convolutional neural network (CNN) based on depthwise separable convolutions, as introduced in the </span> <span>The model used for classification is a convolutional neural network (CNN) based on depthwise separable convolutions, as introduced in the </span>
<a href='https://arxiv.org/pdf/1610.02357' target='_blank' rel='noopener noreferrer'>Xception: Deep Learning with Depthwise Separable Convolutions</a> <a href='https://arxiv.org/pdf/1610.02357' target='_blank' rel='noopener noreferrer'>Xception: Deep Learning with Depthwise Separable Convolutions</a>
<span> paper by François Chollet. It uses who knows how many layers, a dropout and multiple batchnormalsation.</span> <span> paper by François Chollet. The model uses who knows how many layers, a dropout and multiple batchnormalsation.</span>
</div> </div>
</div> </div>
</div> </div>