The machine vision method adopted the discrete cosine transform for autofocus, and then used the image analysis and processing technology to identify and estimate the cell motion parameters. The method is applicable without any discretization or linearization. Processing on board a satellite allows less data to be downlinked. Pengfei Li, Shuiming Wang, Bin Xiong, Xiangbing Tang, Yuxing Tong, Song Gao, Shuangshuang Wen, Ming Huang, Zhoujun Duan, Qianjin Chen. Active learning techniques aim to reduce the total amount of annotation that needs to be performed by selecting the most useful images to label from a large pool of unlabelled images, thus reducing the time to generate useful training datasets. Using Bisection method solve a root of an eq I have no idea on part (b) and (c). Furthermore, we use Matlab package to display 3D surfaces of analytical solutions derived in this study to demonstrate the effect of stochastic term on the solutions of the stochastic-fractional-space AllenCahn equation. Furthermore, the flow behavior is analyzed under the appliance of DarcyForchheimer, activation energy, and chemical reaction. Muhammad Farooq, Zia Ullah, Muhammad Zeb, Hijaz Ahmad, Muhammad Ayaz, Muhammad Sulaiman, Chutarat Tearnbucha, Weerawat Sudsutad. The superiority of this method over the conventional method for uniform thickness treatment is shown through the error and data analysis of the yaw angle, pitch angle, and flying speed. We will find the symmetries and a class of solutions depending on one-parameter ( ) obtained from Lie symmetry groups. The ionosphere of Earth, all physical parameters, such as refractive index, dielectric structure, and conductivity, have a complicated structure. Uses WHU-OPT-SAR-dataset* MFT -> code for 2022 paper: Multimodal Fusion Transformer for Remote Sensing Image Classification* ISPRSS2FL -> code for 2021 paper: Multimodal Remote Sensing Benchmark Datasets for Land Cover Classification with A Shared and Specific Feature Learning Model* HSHT-Satellite-Imagery-Synthesis -> code for thesis - Improving Flood Maps by Increasing the Temporal Resolution of Satellites Using Hybrid Sensor Fusion* MDC -> code for 2021 paper: Unsupervised Data Fusion With Deeper Perspective: A Novel Multisensor Deep Clustering Algorithm* FusAtNet -> code for 2020 paper: FusAtNet: Dual Attention based SpectroSpatial Multimodal Fusion Network for Hyperspectral and LiDAR Classification* AMM-FuseNet -> code for 2022 paper: AMM-FuseNet: Attention-Based Multi-Modal Image Fusion Network for Land Cover Mapping* S1-S2_Transformer -> Sentinel-1 SAR and Sentinel-2 optical timeseries based Transformer architecture for tropical dry forest disturbance mapping* MANet -> code for 2022 paper: MANet: A Network Architecture for Remote Sensing Spatiotemporal Fusion Based on Multiscale and Attention Mechanisms* DCSA-Net -> code for 2022 paper: Dynamic Convolution Self-Attention Network for Land-Cover Classification in VHR Remote-Sensing Images, Measure surface contours & locate 3D points in space from 2D images. For example, the environment temperature and speed range are found difficult to be reached by the current experimental method. First-principle calculations are used to study the electronic structures, electronic and optical properties of pure, phosphorus-doped, aluminum-doped, and phosphorus and aluminum co-doped graphene. In this article, we model the current and voltage across the weak link between two superconductors. They can be used as thermal insulation, structural catalyst supports and energy storage materials. The raw data are relatively uncontrolled, leading to caveats that should guide future, more tailored experiments. Uses WHU-OPT-SAR-dataset* MFT -> code for 2022 paper: Multimodal Fusion Transformer for Remote Sensing Image Classification* ISPRSS2FL -> code for 2021 paper: Multimodal Remote Sensing Benchmark Datasets for Land Cover Classification with A Shared and Specific Feature Learning Model* HSHT-Satellite-Imagery-Synthesis -> code for thesis - Improving Flood Maps by Increasing the Temporal Resolution of Satellites Using Hybrid Sensor Fusion* MDC -> code for 2021 paper: Unsupervised Data Fusion With Deeper Perspective: A Novel Multisensor Deep Clustering Algorithm* FusAtNet -> code for 2020 paper: FusAtNet: Dual Attention based SpectroSpatial Multimodal Fusion Network for Hyperspectral and LiDAR Classification* AMM-FuseNet -> code for 2022 paper: AMM-FuseNet: Attention-Based Multi-Modal Image Fusion Network for Land Cover Mapping* S1-S2_Transformer -> Sentinel-1 SAR and Sentinel-2 optical timeseries based Transformer architecture for tropical dry forest disturbance mapping* MANet -> code for 2022 paper: MANet: A Network Architecture for Remote Sensing Spatiotemporal Fusion Based on Multiscale and Attention Mechanisms* DCSA-Net -> code for 2022 paper: Dynamic Convolution Self-Attention Network for Land-Cover Classification in VHR Remote-Sensing Images, Measure surface contours & locate 3D points in space from 2D images. The results provide ideas for improving the laser damage resistance of the structural surfaces. Code for 2019 paper: Unsupervised Deep Change Vector Analysis for Multiple-Change Detection in VHR Images* hyperdimensionalCD -> code for 2021 paper: Change Detection in Hyperdimensional Images Using Untrained Models* DSFANet -> code for 2018 paper: Unsupervised Deep Slow Feature Analysis for Change Detection in Multi-Temporal Remote Sensing Images* FCD-GAN-pytorch -> Fully Convolutional Change Detection Framework with Generative Adversarial Network (FCD-GAN) is a framework for change detection in multi-temporal remote sensing images* DARNet-CD -> code for 2022 paper: A Densely Attentive Refinement Network for Change Detection Based on Very-High-Resolution Bitemporal Remote Sensing Images* xView2Vulcan -> Damage assessment using pre and post orthoimagery. this is an image of a forest. WebBrowse our listings to find jobs in Germany for expats, including jobs for English speakers or those in your native language. Three different approximation schemes are defined for enhancing the capabilities of volumetric resampling filters. Uses the LEVIR-CD building change detection dataset* INLPGPython -> code for paper: Structure Consistency based Graph for Unsupervised Change Detection with Homogeneous and Heterogeneous Remote Sensing Images* NSPGPython -> code for paper: Nonlocal patch similarity based heterogeneous remote sensing change detection* LGPNet-BCD -> code for 2021 paper: Building Change Detection for VHR Remote Sensing Images via Local-Global Pyramid Network and Cross-Task Transfer Learning Strategy* DSUNet -> code for 2021 paper: Sentinel-1 and Sentinel-2 Data Fusion for Urban Change Detection using a Dual Stream U-Net, uses Onera Satellite Change Detection dataset* SiameseSSL -> code for 2022 paper: Urban change detection with a Dual-Task Siamese network and semi-supervised learning. Academia.edu no longer supports Internet Explorer. WebEnter the email address you signed up with and we'll email you a reset link. JingYan Zheng, Kelaiti Xiao, Bumaliya Abulimiti, Mei Xiang, Huan An. WebEnter the email address you signed up with and we'll email you a reset link. * Intel to place movidius in orbit to filter images of clouds at source - Oct 2020 - Getting rid of these images before theyre even transmitted means that the satellite can actually realize a bandwidth savings of up to 30%* Whilst not involving neural nets the PyCubed project gets a mention here as it is putting python on space hardware such as the V-R3x* WorldFloods will pioneer the detection of global flood events from space, launched on June 30, 2021. Understanding moisture transfer during hot air drying is essential for both quality improvement and energy-efficient dryer design. In the present study, the ion-acoustic solitary wave solutions for KadomtsevPetviashvili (KP) equation, potential KP equation, and Gardner KP equation are constructed. Suitable similarity transformations are used for the transformation of higher order PDEs into the higher order nonlinear ordinary differential equations (ODEs). We study the proposed problem under the Caputo-Febrizo fractional derivative (CFFD). WebThis is the web site of the International DOI Foundation (IDF), a not-for-profit membership organization that is the governance and management body for the federation of Registration Agencies providing Digital Object Identifier (DOI) services and registration, and is the registration authority for the ISO standard (ISO 26324) for the DOI system. This implementation is tuned specifically for satellite imagery and other geospatial raster data* Semantic Segmentation of Satellite Imagery using U-Net & fast.ai -> with repo* clusternetsegmentation -> Unsupervised Segmentation by applying K-Means clustering to the features generated by Neural Network* Collection of different Unet Variant -> demonstrates VggUnet, ResUnet, DenseUnet, Unet. Model accuracy falls off rapidly as image resolution degrades, so it is common for object detection to use very high resolution imagery, e.g. OPEN PHYSICS WELCOMES MINI ARTICLES!For more information please click here, Collaboration with QUANTUM.TECH meeting. OPEN PHYSICS WELCOMES MINI ARTICLES! The dose distributions obtained by the HPBM are in agreement with those obtained by the MC simulations, with a relative error of less than 3% in most of the cases. In addition, there is still no definite principle for the discretization of the model to generate the mesh. Blog post MEET THE WINNERS OF THE OVERHEAD GEOPOSE CHALLENGE* cars -> a dedicated and open source 3D tool to produce Digital Surface Models from satellite imaging by photogrammetry. Also checkout Synthetic data* UAE-RS -> dataset that provides black-box adversarial samples in the remote sensing field* PSGAN -> code for paper: Perturbation Seeking Generative Adversarial Networks: A Defense Framework for Remote Sensing Image Scene Classification* SACNet -> code for 2021 paper: Self-Attention Context Network: Addressing the Threat of Adversarial Attacks for Hyperspectral Image Classification, These techniques combine multiple data types, e.g. The proposal is easily applied in the wave field and other quantities such as temperature, light, and concentration with similar techniques. With repos here and here* Hurricane-Damage-Detection -> Waterloo's Hack the North 2020++ submission. It flags changed areas to prioritise for downlink, shortening the response time* SemiCD -> Code for paper: Revisiting Consistency Regularization for Semi-supervised Change Detection in Remote Sensing Images. The proposed law regarding stress variation and crack propagation in the erosion process in this study contributes to theoretical support for damage detection and service life extension of shield pumps. Stress concentrations typically exist around the perimeter of an opening and on attached structures, thereby resulting in a potential risk of crack initiation. Entry for the EarthNet2021 challenge, The goal is to predict economic activity from satellite imagery rather than conducting labour intensive ground surveys* Using publicly available satellite imagery and deep learning to understand economic well-being in Africa, Nature Comms 22 May 2020 -> Used CNN on Ladsat imagery (night & day) to predict asset wealth of African villages* Combining Satellite Imagery and machine learning to predict poverty -> review article* Measuring Human and Economic Activity from Satellite Imagery to Support City-Scale Decision-Making during COVID-19 Pandemic -> arxiv article* Predicting Food Security Outcomes Using CNNs for Satellite Tasking -> arxiv article* Measuring the Impacts of Poverty Alleviation Programs with Satellite Imagery and Deep Learning -> code and paper* Building a Spatial Model to Classify Global Urbanity Levels -> estimage global urbanity levels from population data, nightime lights and road networks* deeppop -> Deep Learning Approach for Population Estimation from Satellite Imagery, also on Github* Estimating telecoms demand in areas of poor data availability -> with papers on arxiv and Science Direct* satimage -> Code and models for the manuscript "Predicting Poverty and Developmental Statistics from Satellite Images using Multi-task Deep Learning". The machine predicts any part of its input for any observed part, all without the use of labelled data. The model is validated against published results for glucose transport from blood to tissue. 5. Ali Akbar Shaikh, Subhajit Das, Gobinda Chandra Panda, Ibrahim M. Hezam, Adel Fahad Alrasheedi, Jeonghwan Gwak. WebA Fourier transform (FT) is a mathematical transform that decomposes functions into frequency components, which are represented by the output of the transform as a function of frequency. Paper* Flood Segmentation on Sentinel-1 SAR Imagery with Semi-Supervised Learning with arxiv paper* Semi-supervised learning in satellite image classification -> experimenting with MixMatch and the EuroSAT data set* ScRoadExtractor -> code for 2020 paper: Scribble-based Weakly Supervised Deep Learning for Road Surface Extraction from Remote Sensing Images* ICSS -> code for 2022 paper: Weakly-supervised continual learning for class-incremental segmentation* es-CP -> code for 2022 paper: Semi-Supervised Hyperspectral Image Classification Using a Probabilistic Pseudo-Label Generation Framework, Supervised deep learning techniques typically require a huge number of annotated/labelled examples to provide a training dataset. The approach can be extended to treat other kinetic models, while accounting for Fhraeus and FhraeusLindqvist effects in blood microvessels. No.99CH36363), Adaptive Filters In Multiuser (MU) CDMA Detection, Two-Dimensional Set Membership Normalized Least Mean Square Adaptive Channel Estimation for OFDM Systems, Development of fuzzy system based channel equalisers, Accuracy evaluation of fixed-point APA algorithm [adaptive filter applications], Prediction of state transitions in Rayleigh fading channels, Quantizing Input of LMS Algorithm Applied to Noisy Signal Prediction, BioMedSigProcAna Filtering for Removing of Artifacts, Adaptive PD+I Control of a Switch-Mode DCDC Power Converter Using a Recursive FIR Predictor, A Lattice Shalvi-Weinstein Algorithm for Blind Equalization, Consistent estimation of autoregressive parameters from noisy observations based on two interacting Kalman filters, Efficient and Robust Acoustic Feedback Cancellation Algorithm FOR In-car communication system A DISSERTATION SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OFMASTER OF SCIENCE IN SIGNAL PROCESSING IN 2011 Acknowledgments, CONVEX COMBINATION OF BLIND ADAPTIVE EQUALIZERS WITH DIFFERENT TRACKING CAPABILITIES, A New Approach of Performance Analysis of Adaptive Filter Algorithm in Noise Elimination, Reshetov LA Improving channel estimation for rapidly time-varying correlated underwater acoustic channels by tracking the signal subspace, A Two-Stage Approach for Improving the Convergence of Least-Mean-Square Adaptive Decision-Feedback Equalizers in the Presence of Severe Narrowband Interference, A 2-D recursive inverse adaptive algorithm, A Family of Adaptive Filter Algorithms in Noise Cancellation for Speech Enhancement, Adaptive block SSA based ANC implementation for high performances ECG removal from sEMG signals, An efficient recursive total least squares algorithm for FIR adaptive filtering, Limited-precision effects in adaptive filtering, An adaptive correlator receiver for direct-sequence spread-spectrum communication, Efficient online estimation of electromechanical modes in large power systems, Optimal Step-Size LMS Algorithm Using Exponentially Averaged Gradient Vector, Statistical and Adaptive Signal Processing, Performance Analysis of Bayesian Adaptive Filtering, A Two-Stage Approach to Bayesian Adaptive Filtering, Bayesian Adaptive Filtering: Principles and Practical Approaches, Numerically stable fast transversal filters for recursive least squares adaptive filtering, Estimation and equalization of fading channels with random coefficients, Distributed supervised learning using neural networks, Comparison of the RLS and LMS Algorithms to Remove Power Line Interference Noise from ECG Signal, An efficient stabilized fast Newton adaptive filtering algorithm for stereophonic acoustic echo cancellation SAEC, Nonlinear Acoustic Echo Cancellation Based on a Sliding-Window Leaky Kernel Affine Projection Algorithm, Simulation and Performance Analysis of Adaptive Filtering Algorithms in Noise Cancellation, MIMO Receiver Structures with Integrated Channel Estimation and Tracking, Improved elimination of motion artifacts from a photoplethysmographic signal using a Kalman smoother with simultaneous accelerometry, Improving the Tracking Capability of Adaptive Filters via Convex Combination, Avoiding Divergence in the Shalvi–Weinstein Algorithm, Gaussian Processes for Nonlinear Signal Processing, Lecture Notes for a course on System Identification, Performance of multirate CDMA transmission in cellular environment, A Survey with Emphasis on Adaptive filter, Structure, LMS and NLMS Adaptive Algorithm for Adaptive Noise Cancellation System, B 1 0 M ED I CAL SIGNAL ANALYSIS A Case-Study Approach @ R L E N C E. * BoulderAreaDetector -> CNN to classify whether a satellite image shows an area would be a good rock climbing spot or not* ISPRSS2FL -> code for paper: Multimodal Remote Sensing Benchmark Datasets for Land Cover Classification with A Shared and Specific Feature Learning Model. Our key objective in the present work is to elaborate the concept of activation energy in chemically reactive flow with the help of modeling and computation. Adding more concentration of nanoparticles until 5 % 5 \% reduces the nanofluid velocity. This is based on the asymptomatic carriers and symptomatic individuals keeping in view the characteristics of the disease. Solutions are obtained at different fractional orders to discuss the useful dynamics of the targeted problems. The gap between the conduction band and valence band of intrinsic graphene is zero. WebEnter the email address you signed up with and we'll email you a reset link. Analysis of Floyd River flood discharges in James, Iowa, USA, from 1935 to 1973 shows that the proposed model can be quite useful in real applications, especially for extreme value data. The measuring tool used in the article is the Wi-Fi Analyzer App that runs on a smartphone. A weakly-supervised approach, training with only image-level labels* CloudX-Net -> an efficient and robust architecture used for detection of clouds from satellite images* A simple cloud-detection walk-through using Convolutional Neural Network (CNN and U-Net) and fast.ai library* 38Cloud-Medium -> Walk-through using u-net to detect clouds in satellite images with fast.ai* clouddetectionusingsatellitedata -> performed on Sentinel 2 data* Luojia1-Cloud-Detection -> Luojia-1 Satellite Visible Band Nighttime Imagery Cloud Detection* SEN12MS-CR-TS -> code for 2022 paper: A Remote Sensing Data Set for Multi-modal Multi-temporal Cloud Removal* ES-CCGAN -> This is a dehazed method for remote sensing image, which based on CycleGAN* CloudClassificationDL -> Classifying cloud organization patterns from satellite images using Deep Learning techniques (Mask R-CNN)* CNN-based-Cloud-Detection-Methods -> Understanding the Role of Receptive Field of Convolutional Neural Network for Cloud Detection in Landsat 8 OLI Imagery* cloud-removal-deploy -> flask app for cloud removal* CloudMattingGAN -> code for 2019 paper: Generative Adversarial Training for Weakly Supervised Cloud Matting* atrain-cloudseg -> Official repository for the A-Train Cloud Segmentation Dataset* CDnet -> code for 2019 paper: CNN-Based Cloud Detection for Remote Sensing Imager* GLNET -> code for 2021 paper: Convolutional Neural Networks Based Remote Sensing Scene Classification under Clear and Cloudy Environments* CDnetV2 -> code for 2021 paper: CNN-Based Cloud Detection for Remote Sensing Imagery With Cloud-Snow Coexistence* grouped-features-alignment -> code for 2021 paper: Unsupervised Domain Adaptation for Cloud Detection Based on Grouped Features Alignment and Entropy Minimization* Detecting Cloud Cover Via Sentinel-2 Satellite Data -> blog post on Benjamin Warners Top-10 Percent Solution to DrivenDatas On CloudN Competition using fast.ai & customized version of XResNeXt50. Under the DebyeHckel linearization approximation, the semi-analytic solution of the velocity field is derived by Greens function method. The FDM over a randomly generated grid enables fast convergence and improves the accuracy of the solution for a given problem; it also enhances the quality of precision by minimizing the error. These will allow the wave field to be modelled using two techniques: the theoretical shape function and the experimental shape function. With the rapid development of modern high technology and continuous improvement of production technology, stringent requirements have been imposed on modern barrel weapons in terms of precision, range, power, and mobility. There are both closed and open source tools for creating and converting annotation formats. Code for 2019 paper: Unsupervised Deep Change Vector Analysis for Multiple-Change Detection in VHR Images* hyperdimensionalCD -> code for 2021 paper: Change Detection in Hyperdimensional Images Using Untrained Models* DSFANet -> code for 2018 paper: Unsupervised Deep Slow Feature Analysis for Change Detection in Multi-Temporal Remote Sensing Images* FCD-GAN-pytorch -> Fully Convolutional Change Detection Framework with Generative Adversarial Network (FCD-GAN) is a framework for change detection in multi-temporal remote sensing images* DARNet-CD -> code for 2022 paper: A Densely Attentive Refinement Network for Change Detection Based on Very-High-Resolution Bitemporal Remote Sensing Images* xView2Vulcan -> Damage assessment using pre and post orthoimagery. The results showed that the side-entry agitator formed a fountain circulating flow in the stirring tank. In addition, the gravity centre of the charging pile is located at the bottom of the structure, and thus the stability meets the requirements. When this is the case, a technique called zero padding can be used to create two new zero-filled 2N-sample time series {x Z (n)} and {h Z (n)}.Each consists of exact images of the original N-sample time Jiali Zhang, Guangpu Zhao, Na Li, Xue Gao, Ying Zhang. By using suitable similarities, the flow equations are converted into nonlinear ordinary differential equations. This study helps to understand the drying kinetics of P. eryngii slices during the hot air drying and guides the drying process optimization. ImageRegistration-> Interview assignment for multimodal image registration using SIFT* imregdft-> Image registration using discrete Fourier transform. The fractional solutions of PDEs have provided many useful dynamics of the targeted problems. The HPM with suitable boundary conditions results in the so-called HPM solution in general and closed-form, independent of the surface potential. For supervised machine learning, you will require annotated images. Besides high accuracy, it also has many advantages, such as fewer sensors, lower requirement for installation, and larger detection area, by comparison with previous measurement systems. Eurasip Journal on Advances in Signal Processing, 2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE), Circuits and Systems, IEEE Transactions on, 2013 IEEE 4th Latin American Symposium on Circuits and Systems (LASCAS). Three groups of different collision angles were applied to compare and analyze the ozone degradation reaction. Paper* Flood Segmentation on Sentinel-1 SAR Imagery with Semi-Supervised Learning with arxiv paper* Semi-supervised learning in satellite image classification -> experimenting with MixMatch and the EuroSAT data set* ScRoadExtractor -> code for 2020 paper: Scribble-based Weakly Supervised Deep Learning for Road Surface Extraction from Remote Sensing Images* ICSS -> code for 2022 paper: Weakly-supervised continual learning for class-incremental segmentation* es-CP -> code for 2022 paper: Semi-Supervised Hyperspectral Image Classification Using a Probabilistic Pseudo-Label Generation Framework, Supervised deep learning techniques typically require a huge number of annotated/labelled examples to provide a training dataset. Achieves the performance of supervised CD even with access to as little as 10% of the annotated training data* FCCDNpytorch -> code for paper: FCCDN: Feature Constraint Network for VHR Image Change Detection. The results show that the EFM is a promising method to construct abundant analytical solutions for the partial differential equations arising in physics. With additional pre-processing image rotation and scale changes can also be calculated. Using publicly available video of a diffusion cloud chamber with a very small radioactive source, I measure the spatial distribution of where tracks start and consider possible implications. That is, deviations away from 90 result in increased wavefront fluctuations. For the approximations, we use two methods, and analytic perturbation method and the numerical approximation method known as the RungeKutta method. * Object detection on Satellite Imagery using RetinaNet -> using the Kaggle Swimming Pool and Car Detection dataset * Tackling the Small Object Problem in Object Detection * Background reading: Anchor Boxes for Object Detection* Object Detection and Image Segmentation with Deep Learning on Earth Observation Data: A Review* awesome-aerial-object-detection bu murari023, another by visionxiang and awesome-tiny-object-detection list many relevant papers* Object Detection Accuracy as a Function of Image Resolution -> Medium article using COWC dataset, performance rapidly degrades below 30cm imagery* Satellite Imagery Multiscale Rapid Detection with Windowed Networks (SIMRDWN) -> combines some of the leading object detection algorithms into a unified framework designed to detect objects both large and small in overhead imagery. The novel idea is proposed in the mesh generation process, the process to generate random grids. * PASCAL VOC format: XML files in the format used by ImageNet* coco-json format: JSON in the format used by the 2015 COCO dataset* YOLO Darknet TXT format: contains one text file per image, used by YOLO* Tensorflow TFRecord: a proprietary binary file format used by the Tensorflow Object Detection API* Many more formats listed here* OBB: orinted bounding boxes are polygons representing rotated rectangles. This paper describes the model which is run on Intel Movidius Myriad2 hardware capable of processing a 12 MP image in less than a minute* How AI and machine learning can support spacecraft docking with repo uwing Yolov3* exo-space -> startup with plans to release an AI hardware addon for satellites* Sonys Spresense microcontroller board is going to space -> vision applications include cloud detection, more details here* Ororatech Early Detection of Wildfires From Space -> OroraTech is launching its own AI nanosatellites with the NVIDIA Jetson Xavier NX system onboard* Palantir Edge AI in Space -> using NVIDIA Jetson for ship/aircraft/cloud detection & land cover segmentation* Spiral Blue -> startup building edge computers to run AI analytics on-board satellites* RaVAEn -> a lightweight, unsupervised approach for change detection in satellite data based on Variational Auto-Encoders (VAEs) with the specific purpose of on-board deployment.

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