A realtime acoustic bird classification system for the Raspberry Pi 5, based on BirdNET-Pi
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Updated
Feb 17, 2024 - PHP
A realtime acoustic bird classification system for the Raspberry Pi 5, based on BirdNET-Pi
🏁 Flag recognition neural network + flag images dataset
Recognition of the images includes train and tests based on Python.
The C++ neural network for handwritten digit recognition with online demo
Prototype of an intelligent safety system for detecting driver drowsiness
HappyWhale model implementation - Phase B
Recognition of text in images, speech in audio files, recognition of information in PDF!
A Real Time Kurdish handwriting Language Number Recognition Model Using Deep Learning (AlexNet) over used website
A Real Time Kurdish handwriting Language Character Recognition Model Using Deep Learning (AlexNet) over used website
Compare faces from images
An Android app to recognize YOUR hand-writen digits
American Sign Language (ASL) Recognition Project
An Android app to recognize YOUR hand-written Character
As one can predict, many species look visually similar to the untrained eye, so developing software to help non-professionals can bring awareness to the various species. The development of deep learning networks is vital to the improvement of image segmentation when data is being drawn for quantitative purposes.
This notebook uses the classic MNIST handwritten digit dataset, which contains digit 0-9 images of size 28*28. This can be used as self contained program for handwritten digit recognition of a file of data or as pieces to be implemented in other code. This is optimized for greyscale digit recognition.
a custom, class-based reimplementation of LeNet-5, a handwritten digit classifier, in pytorch. model specifications derived from original paper: http://vision.stanford.edu/cs598_spring07/papers/Lecun98.pdf
Diploma project, generating a YOLO model, recognizing people using YOLO, Maixduino microcontroller
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