我正在尝试创建一个包含LoRa E5的跟踪设备。我需要有关电池寿命的帮助。如果我每1分钟跟踪一次设备，LoRa在每个1分钟轨道上消耗多少电流
I am trying to create a tracking device with LoRa E5 in it. I need help with battery life. If I am tracking the device every 1 min, how much current does the LoRa consume on each 1 min track (2024-03-29, Others, 0KB, 下载0次)
试图收集Arcshell AR-5无线电的信息
Trying to gather information on Arcshell AR-5 Radios (2024-03-26, Others, 0KB, 下载0次)
A1收入保证风险覆盖模型
A1 Revenue Assurance Risk Coverage model (2021-09-14, JavaScript, 0KB, 下载0次)
使用用于私有LLM的e5向量嵌入模型的Llama模型的检索增强生成（RAG）
Retrieval Augmented Generation (RAG) for Llama models using e5 vector embedding model for private LLM usage (2023-07-24, Jupyter Notebook, 0KB, 下载0次)
Windows 97中的Clippy回来了！
Clippy from Windows 97 is back ! (2024-01-06, Python, 0KB, 下载0次)
ADRL A1自动编码器和可变自动编码器
ADRL A1 AutoEncoder and Variational AutoEncoders (2023-11-17, Jupyter Notebook, 0KB, 下载0次)
在测试数据上的数字预测精度超过97%。，
digit prediction with more than 97 percent accuracy on test data., (2023-09-16, Jupyter Notebook, 0KB, 下载0次)
空中钢琴：可以用五个手指在空中弹奏从C5到E6的十个音符，2D图像坐标中有21个点，
airpiano: you can play ten notes from C5 to E6 by five fingers in the air with 21 points in 2D image coordinates, (2023-08-24, Others, 0KB, 下载0次)
bf vaeksthuset天体试验，，
bf-vaeksthuset-astro-test,, (2023-08-16, Astro, 0KB, 下载0次)
在kaggle竞争数据集上训练，准确率为97.974%
Trained on kaggle competition dataset with an accuracy of 97.974 % (2019-09-15, Jupyter Notebook, 903KB, 下载0次)
从Automatic1111的webui中的潜在图像浏览服务下载提示
Download prompts from latent image browsing services inside of Automatic1111 s webui (2023-03-15, Python, 7KB, 下载0次)
具有程序难度生成的类似直升机的侧滚动条。
A helicopter-like side scroller with procedural difficulty generation. (2013-01-23, C++, 20KB, 下载0次)
基于SAMD21G的Arduinos的简单音频播放器库。将样本数组发送到A0上的DAC，具有可选的外部...
Simple audio player library for SAMD21G-based Arduinos. Sends an array of samples to the DAC on A0, with optional extrapolation aka oversampling. Intended for playing short sound bites without the need for an external audio player. (2020-12-08, C++, 243KB, 下载0次)
使用TensorFlow 2.0检测枪击的音频分类深度学习模型。测试集准确率97.5%，跟踪率99%...
Audio classification deep learning model using TensorFlow 2.0 to detect Gunshots. 97.5% test set accuracy and 99% training set accuracy was achieved on Binary-Urban8K. This work was done during my summer internship at TUKL-NUST lab. (2020-02-16, Jupyter Notebook, 3842KB, 下载0次)
共现滤波器（CoF）是一种边界保持滤波器，它基于双边滤波器（BF），但不是我们...
Co-occurrence Filter (CoF) is a boundary preserving filter.It is based on the Bilateral Filter (BF) but instead of using a Gaussian on the range values to preserve edges it relies on a co-occurrence matrix. (2018-03-01, Python, 12924KB, 下载0次)
基于干货集中营([http: gank.io api)开放api,采用MVVM架构实现。使用了ViewModel、LiveData等技术](http: gank.io api\)%E5%BC%80%E6%94%BEapi%EF%BC%8C%E9%87%87%E7%94%A8MVVM%E6%9E%B6%E6%9E%84%E5%AE%9E%E7%8E%B0%E3%80%82%E4%BD%BF%E7%94%A8%E4%BA%86ViewModel%E3%80%81LiveData%E7%AD%89%E6%8A%80%E6%9C%AF)
Based on the open api of dry goods concentration camp ([http: gank. io api), it is implemented using MVVM architecture. ViewModel, LiveData and other technologies are used] (http: gank. io api )% E5% BC% 80% E6% 94% BEapi% EF% BC% 8C% E9% 87% 87% E7% 94% A8MVVM% E6% 9E% B6% E6% 9E% 84% E5% AE% 9E% E7% B0% E3% 80% 82% E4% BD% BF% E7% 94% A8% E4% BA% 86ViewModel% E 3% 80% 81LiveData% E7% AD% 89% E6% 8A% 80% E6% 9C% AF) (2019-01-08, Java, 2679KB, 下载0次)
参照[http: yangyi1024.com meizi学习vuejs](http: yangyi1024.com meizi%E5%AD%A6%E4%B9%A0vuejs)
Refer to [http: yangyi1024.com meizi learning vuejs] (http: yangyi1024.com meizi% E5% AD% A6% E4% B9% A0vuejs) (2018-07-16, JavaScript, 145KB, 下载0次)
q3-print2-e6-banco-de-imagens-matheus-araujo-cunha由GitHub课堂创建
q3-sprint2-e6-banco-de-imagens-matheus-araujo-cunha created by GitHub Classroom (2022-03-11, Python, 3KB, 下载0次)
一个橡皮鸭脚本，每60秒从MS Word（97到2003版本）弹出一次Clippy Clippit。由RJ创建...
A rubber-ducky script that pops-up Clippy / Clippit from MS Word (version 97 to 2003) every 60 seconds. Created by RJL Pranks (<http://rjlpranks.com/pranks/clippy>) (2021-05-03, C++, 229KB, 下载0次)
...分类准确率最终达到97.56%。该模型是使用VGG架构构建的...
Constructed a convolutional neural network to classify audio files as being one of the classes [toilet, urinal, sink, unknown]. First a test model was built and trained on an environmental audio dataset called UrbanSounds with 11 sound classes, and a classification accuracy of 97.56% was eventually achieved. The model was built using a VGG (2020-10-04, Python, 1037KB, 下载0次)