Search Results for "smtp-test"
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Showing 12 open source projects for "smtp-test"
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CometAnalyser
CometAnalyser, for quantitative comet assay analysis.
...Once the comets are segmented and classified, several intensity/morphological features are automatically exported as a spreadsheet file. Video Tutorial: CometAnalyser is written in MATLAB. It works with Windows, Macintosh, and UNIX-based systems. Please, download the sample datasets and test it watching the video tutorial to understand how it works: https://www.youtube.com/watch?v=vh2VFnMw50A Contacts: filippo.piccinini85@gmail.com beleonattila@gmail.com -
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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... -
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Machine Learning Homework
Matlab Coding homework for Machine Learning
...Because it is structured as homework or practice material, the code is likely intended more for didactic use than for production deployment. It may contain comments, example datasets, and perhaps test scripts. The repository does not seem to be heavily maintained as a software project; rather, it functions as a library of solved problems and educational examples. The project is useful if you want working MATLAB examples of classic ML techniques, to study, adapt, or compare with your own implementations. -
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VGGFace2
VGGFace2 Dataset for Face Recognition
...The dataset was collected from Google Image Search, ensuring a wide diversity in ethnicity, profession, and real-world conditions. It is split into a training set with 8,631 identities and a test set with 500 identities, making it suitable for benchmarking and large-scale model training. Alongside the dataset, the repository provides pre-trained models based on ResNet-50 and SE-ResNet-50 architectures, trained with both MS-Celeb-1M pretraining and fine-tuning on VGGFace2. These models achieve strong verification performance on benchmarks such as IJB-B and include variants with lower-dimensional embeddings for compact feature representation. ... -
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Coursera Machine Learning
Coursera Machine Learning By Prof. Andrew Ng
CourseraMachineLearning is a personal collection of resources, notes, and programming exercises from Andrew Ng’s popular Machine Learning course on Coursera. It consolidates lecture references, programming tutorials, test cases, and supporting materials into one repository for easier review and practice. The project highlights fundamental machine learning concepts such as hypothesis functions, cost functions, gradient descent, bias-variance tradeoffs, and regression models. It also organizes week-by-week course schedules with links to exercises, lecture notes, and additional resources. ... -
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Faster R-CNN
Object detection framework based on deep convolutional networks
...The Faster R-CNN architecture combines a Region Proposal Network (RPN) with a Fast R-CNN style detection network to share convolutional feature maps and thus speed up detection. The repo includes code to train, test, and deploy Faster R-CNN models under the MATLAB / Caffe environment, example configuration files, and model checkpoints. Multiple configuration files for different datasets and architectures. Evaluation scripts for mAP and detection metrics. -
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This project aims to develop and share fast frequent subgraph mining and graph learning algorithms. Currently we release the frequent subgraph mining package FFSM and later we will include new functions for graph regression and classification package
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mVision library is a set of functions related with computer vision programmed in Matlab. Also include a couple of GUIs for test visually the functions.
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lonestar
A feature selection and classification algorithm based on L1 Norm SVM
A feature selection and classification algorithm. It is based on L1 Norm Support Vector Machine with t-test and Recursive Feature Elimination. -
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Overhead Imagery Research Data Set (OIRDS) - an annotated data library & tools to aid in the development of computer vision algorithms
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Linear Time Invariant (LTI) system identification using particle swarm optimization (PSO) algorithm. Creators : Vahid Kiani, Hadi Sadoghi Yazdi
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k-Nearest Neighbors (kNN) - MATLAB
Complete package
Function 1. classifier_knn 2. accuracy_knn Description 1. Returns the estimated label of one test instance, the k nearest training instances, the k nearest training labels and creates a chart circulating the nearest training instances (chart 2-D of the first two features of each instance). 2. Returns the estimated labels of one or multiple test instances and the accuracy of the estimates.
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