ZHENG's starred repositories
Python-100-Days
Python - 100天从新手到大师
deep-residual-networks
Deep Residual Learning for Image Recognition
computer-vision-in-action
A computer vision closed-loop learning platform where code can be run interactively online. 学习闭环《计算机视觉实战演练：算法与应用》中文电子书、源码、读者交流社区（持续更新中 ...） 📘 在线电子书 https://charmve.github.io/computer-vision-in-action/ 👇项目主页
second.pytorch
SECOND for KITTI/NuScenes object detection
VoiceprintRecognition-Pytorch
This project uses a variety of advanced voiceprint recognition models such as EcapaTdnn, ResNetSE, ERes2Net, CAM++, etc. It is not excluded that more models will be supported in the future. At the same time, this project also supports MelSpectrogram, Spectrogram data preprocessing methods
PointPillars
A Simple PointPillars PyTorch Implementation for 3D LiDAR(KITTI) Detection.
windy-afternoon
Gitbook based Blog, Android, Linux, Deep Learning, Computer Vision
Awesome-Spiking-Neural-Networks
A paper list of spiking neural networks, including papers, codes, and related websites. 本仓库收集脉冲神经网络相关的顶会顶刊论文和代码，正在持续更新中。
Open-Set-Recognition
Open Set Recognition
Multimodal-Learning-with-Alternating-Unimodal-Adaptation
Multimodal Learning Method MLA for CVPR 2024
meta-transformer-amc
Meta-Transformer: A meta-learning framework for scalable automatic modulation classification
SNN-Automotive-Object-Detection
Code of the paper "Efficient Object Detection in Autonomous Driving using Spiking Neural Networks: Performance, Energy Consumption Analysis, and Insights into Open-set Object Discovery"
java_pytorch_onnx_tensorrt_yolov8_vue
基于SpringBoot+Docker+Cuda+Cudnn+Pythorch+Onnx+Tensorrt+Yolov8+ffmpeg+zlmediakit 的AI算法中台系统，本系统主要实现JAVA调用Python脚本的方式，实现在英伟达GPU上进行yolov8的onnx或tensorrt的推理运算，实现火灾烟雾等视频的识别，并将识别结果通过ffmpeg推流到zlmediakit流媒体服务器。
DCASE2023_task2
Submission for task 2 "First-Shot Unsupervised Anomalous Sound Detection for Machine Condition Monitoring" of the DCASE challenge 2023 (https://dcase.community/challenge2023/task-first-shot-unsupervised-anomalous-sound-detection-for-machine-condition-monitoring)
Audio-Classification-based-on-CNN
本项目是在数据集 UrbanSound8K 上进行的音频分类任务，训练 60 个 epoch，最终模型在 10 个类别的整体准确率达到了 98% ，取得了较好的效果。
airport-bird-dataset
A Large-scale Challenging Dataset for Bird Strike Prevention at Real-world Airports