A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
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Updated
Aug 3, 2024 - Python
A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)
Keras model of NSFW detector
Classification models trained on ImageNet. Keras.
InceptionTime: Finding AlexNet for Time Series Classification
food image to recipe with deep convolutional neural networks.
Sign Language Gesture Recognition From Video Sequences Using RNN And CNN
Mobile AI Compute Engine Model Zoo
A neural network to generate captions for an image using CNN and RNN with BEAM Search.
Simple sign language alphabet recognizer using Python, openCV and tensorflow for training Inception model (CNN classifier).
A Multiclass Weed Species Image Dataset for Deep Learning
Detecting Pneumonia in Chest X-ray Images using Convolutional Neural Network and Pretrained Models
COVID-19 Detection Chest X-rays and CT scans: COVID-19 Detection based on Chest X-rays and CT Scans using four Transfer Learning algorithms: VGG16, ResNet50, InceptionV3, Xception. The models were trained for 500 epochs on around 1000 Chest X-rays and around 750 CT Scan images on Google Colab GPU. A Flask App was later developed wherein user can…
Deploying Keras models using TensorFlow Serving and Flask
BEST SCORE ON KAGGLE SO FAR , EVEN BETTER THAN THE KAGGLE TEAM MEMBER WHO DID BEST SO FAR. The project is about diagnosing pneumonia from XRay images of lungs of a person using self laid convolutional neural network and tranfer learning via inceptionV3. The images were of size greater than 1000 pixels per dimension and the total dataset was tagg…
This is the code repository for my Medium post "Understanding your Convolution network with Visualizations"
Supervised Classification of bird species 🐦 in high resolution images, especially for, Himalayan birds, having diverse species with fairly low amount of labelled data [ICVGIPW'18]
Transfer Learning with DCNNs (DenseNet, Inception V3, Inception-ResNet V2, VGG16) for skin lesions classification
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