621 Open source projects that are alternatives of or similar to Bag-of-Visual-Words

Easily train an image classifier and then use it to label/tag other images

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liblinear bindings for Go

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📖 This guide is to help you understand the basics of the computerized image and develop computer vision projects with OpenCV. Includes Python, Java, JavaScript, C# and C++ examples.

利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码

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Audio feature extraction and classification

Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].

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ezSIFT: An easy-to-use standalone SIFT library written in C/C++

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Is This a Joke? Humor Detection in Spanish Tweets

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Large Data Analysis Course Project

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[NeurIPS 2021] DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification

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Support Vector Machine in Javascript

Chatto is a minimal chatbot framework in Go.

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Deep learning, Convolutional neural networks, Image processing, Document processing, Table detection, Page object detection, Table classification. https://www.sciencedirect.com/science/article/pii/S0925231221018142

Classifying time series using feature extraction

✌Real-time translation of the Auslan Alphabet

Our deep learning for computer vision related project for nostalgic poke weebs (Sistemi digitali, Unibo).

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TensorFlow Lite Helper for Android to help getting started with TesnorFlow.

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Performing Leaf Image classification for Recognition of Plant Diseases using various types of CNN Architecture, For detection of Diseased Leaf and thus helping the increase in crop yield.

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This repository consist of a 50-day program. All the statistics required for the complete understanding of data science will be uploaded in this repository.

Visual Similarity research at Fynd. Contains code to reproduce 2 of our research papers.

zAnalysis是基于Pascal语言编写的大型统计学开源库

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Listing my favorite research papers 📝 from different fields as I read them.

采用深度学习方法进行刀具识别。

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An emotion classifier of text containing technical content from the SE domain

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