Image classification: efficientnet/resnest/seresnext/.....
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- Python
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seresnext
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Fully supervised binary classification of skin lesions from dermatoscopic images using an ensemble of diverse CNN architectures (EfficientNet-B6, Inception-V3, SEResNeXt-101, SENet-154, DenseNet-169) with multi-scale input.
deep-learning ensemble-learning densenet convolutional-neural-networks binary-classification inception-v3 senet multi-scale seresnext cyclic-learning-rate skin-lesion-classification shades-of-gray tensorflow-keras color-constancy efficientnet
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Models supported: ResNet, ResNetV2, SE-ResNet, ResNeXt, SE-ResNeXt [layers: 18, 34, 50, 101, 152] (1D and 2D versions with DEMO for Classification and Regression).
demo machine-learning deep-learning pipeline jupyter-notebook python3 resnet regression-models resnext 2d-convolution keras-tensorflow classification-model 1d-convolution seresnet seresnext tensorflow2
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Pytorch implementation of vision models.
python pytorch imagenet resnet transfer-learning pretrained-models resnext seresnet seresnext efficientnet efficientnet-pytorch
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- Python
Detecting Melanoma (skin cancer) using CNNs
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- Python
BirdCLEF 2025 soundscape classification project using deep learning (SeresNeXt26t) with PyTorch, pseudo-labeling, and audio preprocessing for bird species identification.
ml pytorch dl librosa torchaudio seresnext audioclassification kagglecompetitions kagglecompetition birdclef2025 pseudolabeling soundscapeanalysis
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