Search Results for "neural network for image processing matlab code"
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Showing 28 open source projects for "neural network for image processing matlab code"
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Cloud tools for web scraping and data extractionAutomate web data collection with cloud tools that handle anti-bot measures, browser rendering, and data transformation out of the box. Extract content from any website, push to vector databases for RAG workflows, or pipe directly into your apps via API. Schedule runs, set up webhooks, and connect to your existing stack. Free tier available, then scale as you need to.
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AUTOMATIC1111 Stable Diffusion web UI
Stable Diffusion web UI
AUTOMATIC1111's stable-diffusion-webui is a powerful, user-friendly web interface built on the Gradio library that allows users to easily interact with Stable Diffusion models for AI-powered image generation. Supporting both text-to-image (txt2img) and image-to-image (img2img) generation, this open-source UI offers a rich feature set including inpainting, outpainting, attention control, and multiple advanced upscaling options. With a flexible installation process across Windows, Linux, and... -
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MMDeploy
OpenMMLab Model Deployment Framework
...It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN frameworks. Please read getting_started for the basic usage of MMDeploy. -
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Lightweight' GAN
Implementation of 'lightweight' GAN, proposed in ICLR 2021
Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before... -
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DocWire SDK
Award-winning modern data processing SDK in C++20
DocWire SDK, a standout C++20AI driven data processing tool, has received award from SourceForge and strong backing from Microsoft. It handles nearly 100 file types, empowering efficient text extraction, web data extraction, and document analysis. For businesses, the shift to DocWire SDK signifies a leap forward. It promises comprehensive document format support and the ability to extract valuable insights from email boxes, databases, and websites using cutting-edge AI. DocWire SDK aims to... -
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Neural Network Visualization
Project for processing neural networks and rendering to gain insights
nn_vis is a minimalist visualization tool for neural networks written in Python using OpenGL and Pygame. It provides an interactive, graphical representation of how data flows through neural network layers, offering a unique educational experience for those new to deep learning or looking to explain it visually. By animating input, weights, activations, and outputs, the tool demystifies neural network operations and helps users intuitively grasp complex concepts. Its lightweight codebase is... -
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Darknet YOLO
Real-Time Object Detection for Windows and Linux
This is YOLO-v3 and v2 for Windows and Linux. YOLO (You only look once) is a state-of-the-art, real-time object detection system of Darknet, an open source neural network framework in C. YOLO is extremely fast and accurate. It uses a single neural network to divide a full image into regions, and then predicts bounding boxes and probabilities for each region. This project is a fork of the original Darknet project. -
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Real-ESRGAN ncnn Vulkan
NCNN implementation of Real-ESRGAN
Real-ESRGAN ncnn Vulkan is an optimized, cross-platform implementation of Real-ESRGAN using the ncnn neural network inference engine and Vulkan for hardware acceleration. Unlike the standard PyTorch-based Real-ESRGAN code, this variant is written in C/C++ and designed to run efficiently on many platforms (including Windows, Linux, and possibly Android) without requiring heavy frameworks like CUDA or Python. It provides command-line tools for upscaling images with selected models, allowing... -
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cnn-for-image-retrieval is a research-oriented project that demonstrates the use of convolutional neural networks (CNNs) for image retrieval tasks. The repository provides implementations of CNN-based methods to extract feature representations from images and use them for similarity-based retrieval. It focuses on applying deep learning techniques to improve upon traditional handcrafted descriptors by learning features directly from data. The code includes training and evaluation scripts that...
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fastNLP
fastNLP: A Modularized and Extensible NLP Framework
...Provide a variety of neural network components and recurrence models (covering tasks such as Chinese word segmentation, named entity recognition, syntactic analysis, text classification, text matching, metaphor resolution, summarization, etc.). Trainer provides a variety of built-in Callback functions to facilitate experiment recording, exception capture, etc. -
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PRMLT
Matlab code of machine learning algorithms in book PRML
...It also requires Statistics Toolbox (for some simple random number generator) and Image Processing Toolbox (for reading image data). The code is extremely compact. Minimizing code length is a major goal. As a result, the core of the algorithms can be easily spotted. Many tricks for speeding up Matlab code are applied (e.g. vectorization, matrix factorization, etc.). Usually, functions in this package are orders faster than Matlab builtin ones (e.g. kmeans). ... -
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PyTorch Natural Language Processing
Basic Utilities for PyTorch Natural Language Processing (NLP)
PyTorch-NLP is a library for Natural Language Processing (NLP) in Python. It’s built with the very latest research in mind, and was designed from day one to support rapid prototyping. PyTorch-NLP comes with pre-trained embeddings, samplers, dataset loaders, metrics, neural network modules and text encoders. It’s open-source software, released under the BSD3 license. With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. ... -
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ResNeXt
Implementation of a classification framework
ResNeXt is a deep neural network architecture for image classification built on the idea of aggregated residual transformations. Instead of simply increasing depth or width, ResNeXt introduces a new dimension called cardinality, which refers to the number of parallel transformation paths (i.e. the number of “branches”) that are aggregated together. Each branch is a small transformation (e.g. bottleneck block) and their outputs are summed—this enables richer representation without excessive parameter blowup. ... -
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Simd
High performance image processing library in C++
The Simd Library is a free open source image processing library, designed for C and C++ programmers. It provides many useful high performance algorithms for image processing such as: pixel format conversion, image scaling and filtration, extraction of statistic information from images, motion detection, object detection (HAAR and LBP classifier cascades) and classification, neural network. -
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SFD
S³FD: Single Shot Scale-invariant Face Detector, ICCV, 2017
S³FD (Single Shot Scale-invariant Face Detector) is a real-time face detection framework designed to handle faces of various sizes with high accuracy using a single deep neural network. Developed by Shifeng Zhang, S³FD introduces a scale-compensation anchor matching strategy and enhanced detection architecture that makes it especially effective for detecting small faces—a long-standing challenge in face detection research. The project builds upon the SSD framework in Caffe, with... -
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Accord.NET Framework
Scientific computing, machine learning and computer vision for .NET
The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono. -
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GTK+ IOStream
GTK+iostream, Data plots, ORB, Neural Networks, WSOLA
Create GTK+ interfaces using IOStream style code. Its simple and quick! Also providing simple data plotting (similar to Matlab/Octave), ORB (Object Request Broker), and Neural Network computations. You can create GTK+ GUIs in a few lines of code. Labels<<"Thanks for reading"; (HBox<<Labels).show(); or even one line : (HBox() << (Labels()<<"Thanks for reading")).show(); Inline code destructs the classes, but leaves the widgets/callbacks operating. ... -
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CRFasRNN
Semantic image segmentation method described in the ICCV 2015 paper
CRF-RNN is a deep neural architecture that integrates fully connected Conditional Random Fields (CRFs) with Convolutional Neural Networks (CNNs) by reformulating mean-field CRF inference as a Recurrent Neural Network. This fusion enables end-to-end training via backpropagation for semantic image segmentation tasks, eliminating the need for separate, offline post-processing steps. -
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Awesome Recurrent Neural Networks
A curated list of resources dedicated to RNN
A curated list of resources dedicated to recurrent neural networks (closely related to deep learning). Provides a wide range of works and resources such as a Recurrent Neural Network Tutorial, a Sequence-to-Sequence Model Tutorial, Tutorials by nlintz, Notebook examples by aymericdamien, Scikit Flow (skflow) - Simplified Scikit-learn like Interface for TensorFlow, Keras (Tensorflow / Theano)-based modular deep learning library similar to Torch, char-rnn-tensorflow by sherjilozair, char-rnn... -
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DeepDream
This repository contains IPython Notebook with sample code
DeepDream is a small, educational repository that accompanies Google’s original “Inceptionism” blog post by providing a runnable IPython/Jupyter notebook that demonstrates how to “dream” through a convolutional neural network. The notebook shows how to take a trained vision model and iteratively amplify patterns the network detects, producing the hallmark surreal, hallucinatory visuals. It walks through loading a pretrained network, selecting layers and channels to maximize, computing gradients with respect to the input image, and applying multi-scale “octave” processing to reveal fine and coarse patterns. ... -
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ANNGD
Artificial neural network gender detection
ANNGD is a artificial neural network gender detection application. The detection is made in real time images captured by webcam by opencv library. The package include applications to image pre-processing and artificial neural network back-propagation training. -
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ApproxAdderLib
Library of Approximate Adders
...These MATALB and Verilog models can allow software programmer as well as hardware designers to evaluate their code and design. To the best of our knowledge, this is the first open-source library of approximate adders that facilitates reproducible comparisons and further research and development in this direction across various layers of design abstraction. This work is a result of collaborative effort between Chair for Embedded Systems (CES) at Karlsruhe Institute of Technology (KIT), Germany and Vision Image and Signal Processing (VISpro) Lab at SEECS-NUST, Pakistan. -
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neuranep
Neural Network Engineering Platform
...This project is a fork of SpikeOS (sourceforge.net/projects/spikeos) and represents a major update to that code base, including a scripting interface and low-level rewrite of several components. SpikeOS was oriented towards computational modeling. NeuraNEP is oriented toward neural network research. -
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cCNN
A fast implementation of LeCun's convolutional neural network
Code of this library is partialy based on myCNN MATLAB class written by Nikolay Chemurin. -
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...Finding patient disease started by taking Fourier transform (FFT) from input signal and extract a single cycle. Based on some heuristic algorithm the most important feature like P , Q , R , S , T captured and feed to trained neural network. and so the final decision made by CNN library. As mentioned before this software also capable do some image processing on scanned paper to lower the final costs.
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Face recognition using BPNN. Contains 1.Face recognition using Back propagation neural network (customize code) code using matlab. 2. Face recognition using Back propagation network (builtin) code using matlab.Project closed for now,Adeel Raza Azeemi
