Lightweight Neural Network for Semantic Segmentation using Knowledge Distillation (Accepted by AICAS 2022)
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Updated
May 16, 2022 - Python
Lightweight Neural Network for Semantic Segmentation using Knowledge Distillation (Accepted by AICAS 2022)
Some Class Activation Map methods implemented in Pytorch for CNNs
Tutorial to show how to extract object localization
This work study the "Activation/Saliency Map" in image classification, which emphasize the regions in a image where model focus on to give the final predication result.
saliency map, adversarial image, (gradient) class activation map
MVA Master School Project - Weakly Supervised Semantic Segmentation
Class Activation Map (CAM and Grad-CAM) Analysis of fine-tuned CNNs with transfer learning for Pokemon classification task to understand the features learned by deep CNN
Class activation maps for high risk and low risk patients in lung adenocarcinoma
Computer tomography (CT) scans are one of the only ways to diagnose lung diseases. With the rise of lungrelated issues in recent times, it would be a boon if a system existed that would aid medical professionals to diagnose diseases from chest CT scans. This paper proposes to develop such a system in the form of two separate modules using basic …
Enhanced CNN model for malaria cell classification, featuring Class Activation Mapping (CAM) as a non-agnstic technique for anomaly localization and LIME (Local Interpretable-agnostic Explanation) for interpretability, ensuring high accuracy and transparent AI diagnostics.
High Resolutions Class Activation Maps usage script. Implementation from HR-CAM paper.
Detecting Severe Malaria Anaemia and investigating the morphological characteristics of red blood cells at its presenc
A collection of my Jupyter notebooks, showcasing my exploration and learning journey in the field of Computer Vision
Repository for the paper "Neural Networks for Classification and Unsupervised Segmentation of Visibility Artifacts on Monocular Camera Image"
Visualizing Class Activation Maps for Convolutional Neural Networks
Special Project - CA classification (2019 Fall)
A Class Activation Map is a weighted activation map generated for each image, helping us to identify the region a CNN is looking at while classifying an image.
Computer Vision with PyTorch for Medical Image Analysis
Generates class activation maps for CNN's with Global Average Pooling Layer Keras
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