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| basement | related information |
|---|---|
| vscode | vscode |
| Linux | Linux |
| Git | Git |
| Markdown | Markdown |
| Python | Python |
| C | C |
| C++ | C++ |
| Miniconda | Miniconda |
| Server服务器教程 | Server-connection |
| WSL2(教程) | [WSL2] |
| Chatgpt | [Chatgpt] |
| netron(神经网络可视化工具) | [netron] |
- 详情点击这里
- 以下列出已有系列
| brand_name | related information |
|---|---|
| stm32F1-series | |
| stm32F2-series | |
| stm32F3-series | |
| stm32F4-series | |
| stm32F7-series | |
| stm32H5-series | |
| stm32H7-series | |
| stm32G4-series | |
| TC26x | |
| RK3568 | |
| RK3588 | |
| wch32 | |
| stc32 | |
| control_algorithm | related information | code_example(C or CPP) |
|---|---|---|
| PID | [PID_c_best],[PID_h_best];PID1_c,PID1_h;[PID2_c],[PID2_h]； | |
| MPC | [MPC_c_best],[MPC_h_best];[MPC1_c],[MPC1_h];[MPC2_c],[MPC2_h]； | |
| LQR | [LQR_c_best]，[LQR_h_best];[LQR1_c],[LQR1_h];[LQR2_c],[LQR2_h]； | |
| Kalman_filter(卡尔曼滤波) | [Kalman_filter_c_best]，[Kalman_filter_h_best];kalman_filter1_c,kalman_filter1_h;[kalman_filter2_c],[kalman_filter1_h]； | |
| Quaternion(四元素陀螺仪解算) | [Quaternion_c_best]，[Quaternion_h_best];Quaternion1_c,Quaternion1_h;[Quaternion2_c],[Quaternion2_h]； | |
| losspass_filter(低通滤波) | [lowpass_filter_c_best],[lowpass_filter_h_best];lowpass_filter1_c,lowpass_filter1_h;[lowpass_filter2_c],[lowpass_filter2_h] | |
| I2C | I2C_hal_cI2C_hal_h | |
| CAN | ||
|步进电机(tb6600驱动) | | | |直流减速电机(tb6612驱动) | | | |大疆M2006&&M3508(C610&C620-CAN) | | | |大疆M6020(C630-CAN) | | | | | | | | | | | | | | |
| model | Paper | CODE |
|---|---|---|
| YOLO-series | YOLOv1;YOLOv2;YOLOv3;YOLOv4;YOLOv5; | [YOLOv1];YOLOv2;YOLOv3;YOLOv4;YOLOv5; |
| [YOLOv6];[YOLOv7];[YOLOv8];[YOLOv9]; | YOLOv6;YOLOv7;YOLOv8;YOLOv9;YOLOv5lite | |
| Resnet(Deep Residual Learning for Image Recognition) | Resnet; | Resnet; |
| RDN(Residual Dense Network for Image Super-Resolution) | RDN; | RDN; |
| ELC(Efficient Layer Compression Without Pruning) | ELC; | [ELC]; |
| GhostSR(GhostSR: Learning Ghost Features for Efficient Image Super-Resolution) | GhostSR | [GhostSR] |
| CNN(Gradient-Based Learning Applied to Document Recognition) | CNN | [CNN] |
| RCNN(Rich feature hierarchies for accurate object detection and semantic segmentation) | RCNN | [RCNN] |
| Fast R-CNN | Fast_R-CNN | [Fast_R-CNN] |
| Faster R-CNN(Towards Real-Time Object Detection with Region Proposal Networks) | Faster_R-CNN | [Faster_R-CNN] |
| DPM(Object Detection with Discriminatively Trained Part Based Models) | DPM | [DPM] |
| Mark R-CNN | Mark R-CNN | [Mark_R-CNN] |
| Vision Transformer( AN IMAGE IS WORTH 16X16 WORDS: TRANSFORMERS FOR IMAGE RECOGNITION AT SCALE) | Vision_Transformer | [Vision_Transformer] |
| Unet(Convolutional Networks for Biomedical Image Segmentation) | Unet | [Unet] |
| DETR(End-to-End Object Detection with Transformers) | DETR | [DETR] |
| model | Paper | CODE |
|---|---|---|
| Transformer | Transformer | [Transformer] |