deepneuralnetworks

IoBT-VISTEC/EEGANet

EEG Artifact Removal Using Deep Learning (source code, IEEE Journal of Biomedical and Health Informatics)

Prajwal10031999/Plant-Diseases-Classification-using-AlexNet

A deep learning CNN model to predict diseases in plants using the famous AlexNet architecture

Arcadianlee/Deep-Learning-Design-Photonic-Crystals

Modeling and designing Photonic Crystal Nanocavities via Deep Learning

duncangrubbs/lyrics-to-artist

Finding a Artists Style

iambankaratharva/Weapon-Detection

Detection of people and weapons from video footage or images. The detection time was 30ms - 35ms per frame with Darknet-YOLOv4. A custom dataset was used for the training of the object detection model and data integration was performed using OIDv4 ToolKit.

cdalsania/Credit_Card_Fraud_Detection

This project researched the credit card transaction dataset and tried various machine learning classification models on the dataset to determine the best model that would flag suspicious activity more accurately.

chhayac/Gender-Classification-Using-Images

Gender Prediction from Social Media profile pictures using Deep Learning

Sanky18/Crack-Detection-Model

Concrete cracking is a major issue in Bridge Engineering. Detection of cracks facilitates the design, construction and maintenance of bridges effectively.

ultralytics/magellan

Earth observation software powered by Machine Learning (ML). Viewable in Google Maps and WebGL Earth.

valentinarodrigues/Generating_Image_Description

Semantic Description of Images- A deep learning model for describing images using natural language.

AdityaTheDev/ConvolutionalNeuralNetwork-To-Classify-DogVsCat

Convolutional Neural Network to Classify Dogs and Cat. I built a ImageClassifier which classifies and tells you whether its a Dog image or a Cat image. I built a convolutional network which consists of Three Convolution layer and Three MaxPooling layer. Each Convolutional layer has filters, kernel size. Maxpooling layer has stride and pooling size. Then this Convolutional layer Connects to DeepNeuralNetwork. DNN has three hidden layer and output layer having Sigmoid Activation function. I trained this model for 31 epochs and achieved an accuracy of around 85%. I found this massive image dataset online which has 10,028 images(Ten Thousand and Twenty Eight). My model Predicted accurately during the testing phase. I even tested my model using my neighbor dog's pic and it predicted accurately.

akshayush/FeedForward-and-BackPropagation-DNN-for-multiclass-classification

humanunsupervised/deeplearning

A collection of deep learning projects and code from Human Unsupervised.

justanhduc/SRCNN

An implementation of SRCNN

saife245/DEEP-LEARNING-PROJECTS

drewlr/pytorch_intro

NavuluriBalaji/Design-and-Evaluation-of-a-Deep-Learning-Model-for-Counting-Objects-in-Satellite-Images

This study proposes the design and evaluation of a deep learning model using YOLOv8, an advanced object detection algorithm, for object detection and counting in satellite images

NewbieAI/Deep-Neural-Net-Practice

Practice building different deep neural net models starting with simple problems

rlone2018/Tensorflow-Coursera

DeepLearning.AI TensorFlow Developer Professional Certificate Specialization

SanyaGera/Breast-Cancer-Classification-with-Deep-Learning

This is a deep learning model used to identify whether a particular type of breast cancer is malignant or benign. It takes 30 features like area, texture, perimeter etc. in input and based on that features does the required classification. The project involves making deep neural network and training and testing the model with the help of data available from load breast cancer dataset.

karanchaparwal/Sentimental_analysis_IMDB_DNN

Sentimental analysis on IMDB using tflearn Deep Neural Network

kaustubholpadkar/Digit-Recognizer-Keras-DNN

Digit-Recognizer | Kaggle Competition | Keras | Deep Learning