deep learning
Projects with this topic
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This project is a re-implementation of FeatureNet using Tensorflow 2. With working segmentation code.
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This is a project to train, use and analyze 2D and 3D neural networks for segmentation.
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Python application, built on top of Keras, that helps doctors classify breast tumors as benign or malignant, by using ANN architecture and Logistic + Softmax regression. Conducted a small study on how different predictive models can deliver different performances in breast tumor prediction through Deep Learning.
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Benchmarking framework for machine learning with fNIRS
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Image Tagger is an application that predicts an image's tags using deep-learning. It is useful for photographers who want to improve their workflow by auto-tagging images.
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Darknet got illuminated by PyTorch ~ Meet Lightnet
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This is the unpaired image-2-image and volume-2-volume translation project. It converts images or volumes of an input domain to a target domain using artificial intelligence.
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This project provides a deep learning approach to learn machining features from CAD models using a hierarchical graph convolutional neural network.
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Developed a project utilizing Generative Adversarial Networks (GANs) to convert grayscale images to RGB color images. Leveraged deep learning techniques to train the GAN model on a dataset of grayscale and corresponding color images, achieving realistic colorization results. This project demonstrated proficiency in image-to-image translation and advanced deep learning methodologies within the realm of computer vision.
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Real-time Gender and Age Recognition from Audio
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FakET: Simulating Cryo-Electron Tomograms with Neural Style Transfer
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ICT deep learning lab
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End-to-end meme template extractor & enhancer
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Controversy quantification of topics on twitter, based on user probability to participate in a controversy topic, using GNN and NLP models.
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Generate ALT text (captions for low vision website users or book readers).
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A trainable AI with data in text format. Deterministic
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The aim of this project is to provide an exploratory analysis of Domain Adaptation (DA) techniques in the context of PHM for Bearings fault prognosis, focusing on Health Index (HI) estimation and Remaining Useful Life (RUL) prediction. The adopted dataset is the PRONOSTIA/FEMTO-ST bearings dataset.
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