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clip_for_dml

CLIP Feature Extractor and Linear Projection Loss for Deep Metric Learning

currency-prediction-by-probability-patterns

diffusion_segmentation

Use denoising diffusion model to segment the objects on the image step by step.

dinov2

PyTorch code and models for the DINOv2 self-supervised learning method.

dml_segmentation

eth_price_prediction_with_sinewaves

few_shot_sam

FEWSAM Few-shot Segmentation tool based on Segment Anything

filter_distinguisher

A CNN Model that creates filters bu unsupervised learning. The model tries to distinguish the output of each convolution operation and tries to create filters that generate most various output layers.

guided_segmentation

One way Few-shot Segmentation

image_to_image_syntetic_data_generator

A synthetic data generator using stable diffusion, it works with image inputs instead of text input

mpnn_on_imagenet

Multi-Perspective Neural Networks(MPNN) applied on ImageNet dataset. MPNN is a unsupervised learning algorithm.

objectdetectionsilverbullet

Clean and basic implementation of retinanet object detection.

objectron

Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes

qsnn

Entangled state prediction with respect to time

rgb2spherical

rootvision

segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

self_supervised_learning_linear_projection

A Self Supervised Learning Method using Linear Projection

semantic_segmentation

sinusoidal_neural_networks

Feed-forward neural network model using w_oxsin(w_ixpi) instead of using w*x+b as basis function.

sinusoidal_neural_networks_experiments_4_1

Experiments which are conducted in Section 4.1 in master thesis "Development of Deep Neural Networks that learns faster"

sinusoidal_neural_networks_experiments_5_4

Experiments which are conducted in Section 5.4 in master thesis "Development of Deep Neural Networks that learns faster"

solo-learn

solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning

spelling-error-correction-censor-bad-words-using-prime-numbers

vectorsum_vectordifference

A Self-supervised learning algorithm that uses summation and difference of embedding vectors that are generated from partial and full image.