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a-simplified-framework-for-zero-shot-cross-modal-sketch-data-retrieval

We deal with the problem of zero-shot cross-modal image retrieval involving color and sketch images through a novel deep representation learning technique.

ann_gpu

Neural Network from scratch Using CUDA

awesome-satellite-imagery-datasets

🛰️ List of satellite image training datasets with annotations for computer vision and deep learning

canny-edge-detector

Implementation of Canny edge detector

classification-of-housing-data

Using sklearn, in Python. Implementation includes Random forest and XGBoost classifier.

cmir-net-a-deep-learning-based-model-for-cross-modal-retrieval-in-remote-sensing

We address the problem of cross-modal information retrieval in the domain of remote sensing. In particular, we are interested in two application scenarios: i) cross-modal retrieval between panchromatic (PAN) and multispectral imagery, and ii) multi-label image retrieval between very high resolution (VHR) images and speech-based label annotations. These multi-modal retrieval scenarios are more challenging than the traditional uni-modal retrieval approaches given the inherent differences in distributions between the modalities. However, with the increasing availability of multi-source remote sensing data and the scarcity of enough semantic annotations, the task of multi-modal retrieval has recently become extremely important. In this regard, we propose a novel deep neural network-based architecture that is considered to learn a discriminative shared feature space for all the input modalities, suitable for semantically coherent information retrieval. Extensive experiments are carried out on the benchmark large-scale PAN - multispectral DSRSID dataset and the multi-label UC-Merced dataset. Together with the Merced dataset, we generate a corpus of speech signals corresponding to the labels. Superior performance with respect to the current state-of-the-art is observed in all the cases.

context-attended-graph-convolution-network

Context-attended Graph Convolution Network for Remote Sensing Images

crossatnet-a-novel-cross-attention-based-frameworkfor-sketch-based-image-retrieval

doodle2search

Doodle to Search: Practical Zero Shot Sketch Based Image Retrieval

dual-path-morph-unet

dummy_images

earth-on-canvas-dataset

Sketch-based aerial image retrieval

fine-tuning-and-feature-extraction-from-pretrained-models

In this example, we use the pre-trained ResNet50 model, which is pretrained on the ImageNet dataset. The implementation is in TensorFlow-Keras.

hsiconvkan

How to Learn More? Exploring the Possibility of Kolmogorov-Arnold Networks for Hyperspectral Image Classification

image-to-region-adjacency-graph-creation

Convertion of an RGB image to a Region Adjacency Graph (RAG) using SLIC super-pixel based segmentation technique.

isothetic-covers

Isothetic covers and convex hull for character recognition

logo-segmentation

machinelearning

Code repository for the C-MInDS, IIT Bombay course.

multi-label-analysis

multi-view-information-bottleneck

Implementation of Multi-View Information Bottleneck

presentations

pygcn

Graph Convolutional Networks in PyTorch

pytorch-bayesiancnn

Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

remote-sensing-datasets

A list of radar and optical satellite datasets for detection, classification, semantic segmentation and instance segmentation tasks.

satellite-imagery-datasets-containing-ships

A list of radar and optical satellite datasets for ship detection, classification, semantic segmentation and instance segmentation tasks.

ship-detection-challenge

siamese-spatial-graph-convolution-network

Siamese graph convolutional network for content based remote sensing image retrieval

simclr

A SimCLR implementation for self-supervised learning from unlabeled data

tsne-plot-and-bar-graphs

Essential codes for result analysis

ucmerced-speech-audio-samples