Fast and accurate AI powered file content types detection
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Updated
Dec 1, 2025 - Python
Fast and accurate AI powered file content types detection
Collection of Keras models used for classification
Keras implementation of a ResNet-CAM model
Distributed Keras Engine, Make Keras faster with only one line of code.
K-CAI NEURAL API - Keras based neural network API that will allow you to create parameter-efficient, memory-efficient, flops-efficient multipath models with new layer types. There are plenty of examples and documentation.
Object classification with CIFAR-10 using transfer learning
CΓ³digos Python com diferentes aplicaΓ§Γ΅es como tΓ©cnicas de machine learning e deep learning, fundamentos de estatΓstica, problemas de regressΓ£o de classificaΓ§Γ£o. Os vΓdeos com as explicaΓ§Γ΅es teΓ³ricas estΓ£o disponΓveis no meu canal do YouTube
Classify movie posters by genre
We pit Keras and PyTorch against each other, showing their strengths and weaknesses in action. We present a real problem, a matter of life-and-death: distinguishing Aliens from Predators!
Implemented two papers for offline signature verification. Both use different deep learning techniques - Convolutional network and Siamese network.
Classifying 10 different categories of Sound using Deep Learning.
Source code for the paper "Reliable Deep Learning Plant Leaf Disease Classification Based on Light-Chroma Separated Branches".
Make a graph network of your followers. Based on username and gender
Classification of Time-series data with RNN
Source code for the paper "Color-aware two-branch DCNN for efficient plant disease classification".
QReLU and m-QReLU: Two novel quantum activation functions for Deep Learning in TensorFlow, Keras, and PyTorch
Multiple Handwritten Digit Recognition app Using Deep Learing - CNN from Canvas build on tkinter- GUI
RNN classifier built with Keras to classify MNIST dataset
AI Nexus π is a streamlined suite of AI-powered apps built with Streamlit. It features π StyleScan for fashion classification, π©Ί GlycoTrack for diabetes prediction, π’ DigitSense for digit recognition, πΈ IrisWise for iris species identification, π― ObjexVision for object recognition, and π GradeCast for GPA prediction with detailed insights.
Dataset + convolutional neural network for recognizing Italian Sign Language (LIS) fingerspelling gestures
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