2:22
A I for robot
Minh Tuấn Nguyễn Trần
3:24
Humanoid Robot
0:48
QT + OpenCV + Tensorflow
0:27
Select object tracking
46:50
1. Training and Predict Model
41:43
2. Generate Data from directory
5:31
3. Automatic labeling common object use Yolo
49:41
4_1. Transfer Learning
7:21
4_2. Japanese book detect using transfer learning
20:25
01. Pytorch - Basic 1
4:34
02. Pytorch - Gradient and backward()
4:49
OpenCV DNN YoloV4
12:08
OpenCV DNN C++ Object Detection - MobileNet
4:32
OpenCV DNN C++ - Classification
11:55
ONNX Js - Classification
3:54
TorchViz - Show computational graph
15:40
03. Pytorch - Build neuron network
5:50
Head Pose Estimation - Dlib, OpenCV and mediapipe
2:45
OpenCV Mouse CallBack C++
8:20
OpenCV Matrix
8:47
Face(detection) + Gender(Classification) + Age(Classification) - Deep Learning with OpenCV
5:38
OpenCV - blend and alphaBlendDirectAccess
11:31
Semantic Segmentation - Background and Fore Ground Processing
5:21
Augmented Reality With Aruco Markers
1:59
OpenCV Blob Detector
6:25
OpenCV Camera Calibration - Intrinsic and Extrinsic
2:52
OpenCV - PCACompute for Eigen Face
7:53
Arc Face Model
6:18
Face Detection Comparison - Non Network (HaarCascase, HoG) and NN(CNN and ResNet)
5:13
Face Landmark to add Mask
3:13
Face Morph - Morph Triangle
3:25
OpenCV Face Swap
6:02
Deep Learning - Hand Pose
1:43
openCV - Find Homography and Warp Perspective
4:33
Object detection Server: Yolov4 and Flask
20:17
03. Pytorch - nn.Module
7:36
04. Pytorch - nn.Sequential
20:18
05. Pytorch - Load Model and Predict Image
28:28
[Tensorflow] Tensorflow Run Time - FP32 + FP16 + INT8
10:52
[Tensorflow] TF-Lite
2:34
[Tensorflow] TF-Lite - Leaky Relu
16:16
07. [Pytorch] - Object detection - Theory
2:01:33
08. Pytorch - DataLoader, Augmentation, getDataList - Object Detection
3:12:38
08. Pytorch - Object Detection - Training and Inference
22:06
09. Pytorch - PSPNet Segmentation - Demo and Theory
1:39:15
10.Pytorch - PSPNet Model and Training
1:42:16
06. Pytorch - Image Classification
28:13
01. Keras and Deep Learning Math
2:58
02. Keras - Linear Regression (With and without keras)
21:04
03. Keras - Mnist
6:36
03. Keras - Scaling input from 0 to 1
5:49
04. Keras - Effect of 0 and 255, feed to model
5:53
05. Keras - Batch size - params update times
4:22
05. Keras - L1/L2 Regularization |w| / w^2
0:03
06. Keras - DropOut - Avoid over-fitting
35:37
Multi Object Tracking not use Deep Learning
0:45
Tensorflow JS - 3D Character Animation
8:14
07. Keras - Old NN (Dense) and new NN ( CNN) comparison
19:05
Tableau for visualize data in BI, Deep Learning or Machine Learning
10:58
Fast framework for choosing and training model fit with data
10:13
Slam Lidar Based
3:38
SLAM Pinhole-Mono-Cam Based
1:11
Wav2Vec run on CPU
0:38
Face Regconication on CPU
22:51
1. Candlestick for finance
31:30
2. Indicator in finance: SMA, MACD, RSI, BB, Stochostic Osc, KDJ, Risk managerment to Buy/Sell
3:26
OD-OT-HP-GAN
1:08
Carton Detection and Send Mail in time
2:15
LLaMa chat instruct - Understand image sent
Whisper for Speech2Text
2:26
Social Distance Detection - Activity Detection - Human detection and tracking - GAN style transfer
3:52
News Auto-Bot with N8N and LLM
