Showing 5 open source projects for "matlab diffusion map"

View related business solutions
  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

    Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
    Try It Free
  • Our Free Plans just got better! | Auth0 Icon
    Our Free Plans just got better! | Auth0

    With up to 25k MAUs and unlimited Okta connections, our Free Plan lets you focus on what you do best—building great apps.

    You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
    Try free now
  • 1
    DnCNN

    DnCNN

    Beyond a Gaussian Denoiser: Residual Learning of Deep CNN

    This repository implements DnCNN (“Deep CNN Denoiser”) from the paper “Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising”. DnCNN is a feedforward convolutional neural network that learns to predict the residual noise (i.e. noise map) from a noisy input image, which is then subtracted to yield a clean image. This formulation allows efficient denoising, supports blind Gaussian noise (i.e. unknown noise levels), and can be extended to related tasks like image super-resolution or JPEG deblocking in some variants. The repository includes training code (using MatConvNet / MATLAB), demo scripts, pretrained models, and evaluation routines. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    CAM

    CAM

    Class Activation Mapping

    This repository implements Class Activation Mapping (CAM), a technique to expose the implicit attention of convolutional neural networks by generating heatmaps that highlight the most discriminative image regions influencing a network’s class prediction. The method involves modifying a CNN model slightly (e.g., using global average pooling before the final layer) to produce a weighted combination of feature maps as the class activation map. Integration with existing CNNs (with light...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    ConvNet Burden

    ConvNet Burden

    Memory consumption and FLOP count estimates for convnets

    ...Estimation of memory consumption (e.g. feature map sizes, parameter storage). Support for multiple network definitions/architectures. Estimation of memory consumption (e.g. feature map sizes, parameter storage). Estimation of FLOPs (floating point operations) for CNN architectures.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 4
    Faster R-CNN

    Faster R-CNN

    Object detection framework based on deep convolutional networks

    ...Multiple configuration files for different datasets and architectures. Evaluation scripts for mAP and detection metrics.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Error to trace to log to deploy. One click. No SSH. Icon
    Error to trace to log to deploy. One click. No SSH.

    Catch the cause before the pager goes off.

    AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
    Free 30 days.
  • 5
    HashingBaselineForImageRetrieval

    HashingBaselineForImageRetrieval

    Various hashing methods for image retrieval and serves as the baseline

    This repository provides baseline implementations of deep supervised hashing methods for image retrieval tasks using PyTorch. It includes clean, minimal code for several hashing algorithms designed to map images into compact binary codes while preserving similarity in feature space, enabling fast and scalable retrieval from large image datasets.
    Downloads: 2 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next