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feature-extraction-with-cnns

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SayamAlt / Traffic-Signs-Detection-using-Faster-R-CNN

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Successfully developed an object detection model using Faster R-CNN to detect and classify traffic signs in road images, enhancing autonomous driving and intelligent transportation systems.

computer-vision deep-learning torch pytorch faster-rcnn convolutional-neural-networks object-detection traffic-sign-detection roi-selection torchvision roi-extraction roi-pooling region-proposal-network torchvision-datasets torchvision-model torchvision-transforms feature-extraction-with-cnns
  • Updated Jul 4, 2025
  • Jupyter Notebook

neha-nambiar / Meesho_Data_Challenge

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Ranked 27th on Kaggle Leaderboard in the Visual Taxonomy competition sponsored by Meesho. Built a multi-model system for fashion product attribute prediction from images using ResNet101V2, EfficientNetB0, and ConvNeXt Base, category-specific CatBoost classifiers and class balancing using SMOTE.

computer-vision kaggle-competition resnet multi-model smote catboost efficientnet convnext feature-extraction-with-cnns
  • Updated Mar 30, 2025
  • Jupyter Notebook

SayamAlt / Wind-Turbines-Detection-using-Faster-R-CNN

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Successfully developed an object detection model using Faster R-CNN to detect and localize wind turbines in aerial imagery, aiding in automated monitoring and infrastructure assessment.

computer-vision torch pytorch faster-rcnn convolutional-neural-networks object-detection region-of-interest roi-selection torchvision roi-extraction roi-pooling region-proposal-network torchvision-datasets torchvision-model torchvision-transforms feature-extraction-with-cnns
  • Updated Jul 4, 2025
  • Jupyter Notebook

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