Ayush Thakur
  • About Me
  • Authoring
    • DeepFaceDrawing: An Overview
    • Rewriting a Deep Generative Model: An Overview
    • Unsupervised Visual Representation Learning with SwAV
    • In-Domain GAN Inversion for Real Image Editing
    • Metric Learning for Image Search
    • Object Localization with Keras and W&B
    • Image Segmentation Using Keras and W&B
    • Understanding the Effectivity of Ensembles in DL
    • Modern Data Augmentation Techniques for CV
    • Adversarial Latent Autoencoders
    • Towards Deep Generative Modeling with W&B
    • Interpretability in Deep Learning - CAM and GradCAM
    • Introduction to image inpainting with deep learning
    • Simple Ways to Tackle Class Imbalance
    • Debugging Neural Networks with PyTorch
    • Generating Digital Painting Lighting Effects
    • Multi Task Learning with W&B
    • Translate American Sign Language Using CNN
    • Converting FC Layers to Conv Layers
  • Projects
    • Smart Traffic Management Using Reinforcement Learning
    • Sign Language Translator
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  1. Authoring

Converting FC Layers to Conv Layers

4th July, 2019

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Last updated 4 years ago

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CNN revolutionized image classification task. But their power lies in the fact that they can sustain spatial information, unlike a dense neural network. The spatial information can thus be modified, manipulated and interpolated by computers to understand more from an image and not just classify.

Semantic Segmentation is one such aspect of computer vision and image processing in general whereby every pixel has a story to convey. We humans can judge and infer so many spatial information by looking at an image. The possibilities offered by semantic segmentation opened this door for computers too, thus advancements in technologies like autonomous vehicles.

​😋 Read the article .

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