Binary classification, SHAP (Explainable Artificial Intelligence), and Grid Search (for tuning hyperparameters) using EfficientNetV2-B0 on Cat VS Dog dataset.
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Updated
May 4, 2024 - Jupyter Notebook
Binary classification, SHAP (Explainable Artificial Intelligence), and Grid Search (for tuning hyperparameters) using EfficientNetV2-B0 on Cat VS Dog dataset.
Paper and conference presentation during the 1st year of MSc Data Science & Artificial intelligence
Automated Diagnosis of Pneumonia from Classification of Chest X-Ray Images using EfficientNet
EfficientNetV2 reimplement with Pytorch framework
Image classification convolutional neural network, using TensorFlow with an NVIDIA GPU
EfficientDet in TensorFlow 2.0
EfficientNetV2: Smaller Models and Faster Training. PyTorch Implementation of EfficientNetV2 Family
Train EfficientNetV2 models for Facial Expression Recognition task
DeepLabV3 plus implementation using PyTorch
Outlier Detection and Deep Learning Classification Project
Repository containing Code and other materials for the Research Project on Rock Type Classification
Experiment with Centroid Re-ID by Changing Backbone Using EfficientNet-V2 and Adding Re-Identification Based Data Augmentation
Predict Cervical Cancer with Algoritm EfficientNetV2 Tensorflow and Pythorch
BackdropBuild V3 Program
Final submission project in Belajar Pengembangan Machine Learning by Dicoding Academy about Image Classification Facial Emotion With EfficientNetV2-S Tensorflow
Explorative Computer Vision Project using EfficientNet
Pyramid-based structure for head pose estimation
"DressMeUp" project utilizes fashion images and color combinations to achieve image classification for clothing combinations. Algorithms include SGD (SVM), Passive Aggressive Classifier, ResNet50 CNN, and EfficientNetV2-S CNN with K-Means for color analysis. Achieved accuracy exceeds 90%. Built with Python, Scikit-Learn, TensorFlow, and Streamlit.
This repository holds the downstream task of Face Mask Classification performed on Self Currated Custom Dataset with various State of the Art deep learning models like ViT, BeIT, DeIT, LeViT, ConvNeXt, VGG16, EfficientNetV2, RegNet and MobileNetV3.
Deep Food Image Recognition Project
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