CNN-based Image Classification Project
ImageClassification
Built and trained a custom convolutional neural network (CNN) model on the CIFAR-10 dataset to classify images into 10 categories. Preprocessed the image dataset by normalizing pixel values and visualized training images. Implemented a multi-layer CNN with convolutional, pooling, and dense layers, and evaluated model performance using test accuracy.
• Applied deep learning for supervised image classification tasks
• Utilized Python, TensorFlow, and Keras libraries for model development
• Gained practical experience in image labeling, preprocessing, and evaluation
• Achieved high accuracy in classifying complex visual data
Built and trained a custom convolutional neural network (CNN) model on the CIFAR-10 dataset to classify images into 10 categories. Preprocessed the image dataset by normalizing pixel values and visualized training images. Implemented a multi-layer CNN with convolutional, pooling, and dense layers, and evaluated model performance using test accuracy. • Applied deep learning for supervised image classification tasks • Utilized Python, TensorFlow, and Keras libraries for model development • Gained practical experience in image labeling, preprocessing, and evaluation • Achieved high accuracy in classifying complex visual data
2024 - 2024