idle147

本程序是一个联机版的智能校园防御系统应用程序，用Qt、PYTHON语言编写，在 Windows环境下运行。该系统实现了基于摄像头数据采集、人脸识别、口罩识别、数据统计的预警系统，该项目由模型搭建、客户端、百度AI人脸库程序三大部分构成，项目综合了《嵌入式 AI 平台应用开发》和《Linux 基础开发》的知识体系；采用 OpenCV/爬虫数据采集、利用 Numpy、Pandas 及特征工程、模型聚合进行数据预处理、CNN 模型训练框架。

Language:Python3800

Automated_test_platform

代码是基于徐德晨等前辈撰写的《高效自动化测试平台——设计与开发实战》一书，自己阅读并抄写而成的。同时，在代码里面写了相关注释和学习感悟。仓库内容随着书本的学习深入而更新。

Language:Python300

mask_detection

口罩图片的获取与利用AlexNet模型进行二分类

Language:Python100

Distinguishing_Recolored_Images

With the development of image colorization technique, the recolored images (RIs) become more and more authentic, making it very difficult to visually distinguish from natural images (NIs). Recently, researchers have proposed the detection methods towards recolored images. However, the current detection still has limitations such as poor generalization, large-scale training samples, high-dimensional features for training, and high computation cost. To address those issues, this paper proposes a novel method based on the lateral chromatic aberration (LCA) inconsistency and its statistical differences. Generally, RIs have fewer numbers of LCA characteristics than that of NIs, that inspire us to design the classifier for distinguishing two types of images. In particular, we propose to adopt very low 5-dimensional features to feed a classical SVM mechanism. The baseline ImageNet and Oxford datasets are used to verify the effectiveness of the proposed method, in which the performance of our proposed method rivals the prior arts.

Language:MATLAB200

idle147

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