Convolutional neural network implementation using NumPy
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Updated
Jan 19, 2020 - Python
Computer vision is an interdisciplinary field that deals with how computers can be made to gain high-level understanding of digital images and videos.
Convolutional neural network implementation using NumPy
yolov3, deep_sort and optical flow
Computer vision project implemented with OpenCV
A basket ball shot predictor. It will first track the ball using its contours and based on its initial travelling points, predict whether the shot will land in the basket.
This model was designed around Pycoco's dataset, the CNN model constructed outputs training loss graphs and a confusion matrix for the network of interest
A deep residual neural network in the fashion of ResNet50, capable of completing image classification tasks efficiently. Manually implemented the core layer blocks.
Color Trackbar that is helpful finding Colors lower-range and upper range manually
Experimenting with deep learning to implicitly represent images
Running LED with computer vision and Arduino
CLIP based human action recognition, alignment of text and image using Prompt engineering.
Easy to use, popular computer vision layers' implementations with customizable parameters
Assignment solutions to Standford online course "CS231N - Convolution Neural Networks for Vision Recognition"
Headphones object detection using YoloV4