efficientnetb0

koltaib/Melanoma_Detection

This is a project documentation about melanoma detection methods using convolutional neural networks.

snoop2head/ElimNet

🔪 Elimination based Lightweight Neural Net with Pretrained Weights

LuluW8071/ASL-Alphabet-Detection

American Sign Language Alphabet Detection in Real Time using OpenCV-Mediapipe with EfficientNetB0 in PyTorch

tariqshaban/arabic-sign-language-image-classification

An implementation of the Arabic sign language classification using Keras on the zArASL_Database_54K dataset

Aku02/AI_CPS_IITR

TFlite+CNN

harshd23/Food_Vision

The purpose of Food Vision project is to classify 101 variety of food items using Machine Learning.

kzaleskaa/depth-estimation-with-compression

Development of a depth estimation model based on a UNET architecture - connection of Bi-directional Feature Pyramid Network (BIFPN) and EfficientNet.

amiruzzaman1/Deepfake-Detection

Deepfake detection leveraging the OpenForensics dataset, a comprehensive resource for face forgery detection and segmentation research. The project explores various deep learning models and evaluates their performance in distinguishing between real and fake images of human faces.

Dev-Khant/Image-Captioning

Image Captioning using EfficientNet and GRU

Furkantsnb/CoalClassifie

CoalClassifier: A deep learning model for classifying coal types using EfficientNetB0-based transfer learning and fine-tuning techniques. This project is designed to accurately distinguish between Anthracite, Bituminous, Lignite, and Peat classes and is developed using TensorFlow/Keras

k5iogura/darknetB0-4Y

49.5 mAP50 Detector enet4y2-coco.cfg = EfficientnetB0 + 4YOLO Layers + BiDirectionalFeatureMap with COCO Dataset and 81.0 mAP50 with VOC2007 test Dataset.

msikorski93/Alzheimer-s-Disease-Classification

A multi classification using scikit-learn and TensorFlow models on MRI scans of patient's brains.

sitamgithub-MSIT/MalDetect

A Deep Learning application for Malaria Detection

tmfreiberg/HAM10000-skin-lesion-classification

HAM10000 Skin Lesion Classification

AliTahir-101/finnish-traffic-sign-recognition

Real-time Finnish traffic sign detection and classification using synthetic data, transfer learning, and advanced deep learning techniques.

anhphan2705/mask-wearing-classification

Efficient way to detect if a face has a mask on. Used EfficientNet-B0 model architecture.

Etienne-bobo/food101_classification_tensorflow

The model employs mixed-precision training within the TensorFlow framework, utilizing transfer learning techniques that encompass both feature extraction and fine-tuning stages. This approach is executed on the EfficientNetB0 architecture

ginamartinezl/Vision_Reconocimiento_De_Objetos

Clasificación de imágenes y reconocimiento de objetos mediante la red neuronal convolucional CNN DenseNet y EfficientNet con el modelo frozen model y el framework Coffe. Posteriomente, mediante la red neuronal convolucional CNN MobileNet-SSD y YOLO con el framework TensorFlow

harshdeepkalita/BarkRescue

I'm developing an app named BarkRescue, which includes project code, app functionalities, and system architecture. Additionally, I've written three detailed blogs on EfficientNet, YOLOv5, and MobileNet-v2, focusing on their architecture and workings before integrating these models into my project.

Kailash-Natarajan/INR-CURRENCY-DENOMINATION-RECOGNITION-USING-TRANSFER-LEARNING

INR Denomination Recognition is an image classification project

nouhabenhamada/Image-Classification-Is-it-Real-or-generated-by-AI-

A Streamlit aaplication to distinguish between AI-generated and real images. Utilizing the TensorFlow framework, the core model is based on EfficientNetB0, which has been fine-tuned on a custom dataset containing both fake and real images.

psychoatom/Mask-Monitoring-System

Mask Monitoring System

RidaDogrul/EfficientNetB0_for_transfer_learning

safwanshamsir99/Dust-Detection-CNN

Dust detection on solar photovoltaics panel using pre-trained CNN models

Venn1998/GlaucomaDetection

Development and analysis of various deep NN models to detect glaucoma cases from fundus images. The performance of the best model was evaluated with cross-validation. Mean F1-score: 0.95975, with a standard deviation of 0.02274.

Xza85hrf/Flag_Prediction_Project

This application predicts the name of a country (or countries) based on an input flag image. It uses advanced image processing techniques and deep learning models built with PyTorch to classify flags accurately.

AlvinManojAlex/MStar-SAR

himanshumahajan138/TransferVision

Transfer learning for image classification using pre-trained models like ResNet50, ResNet100, EfficientNetB0, and VGG16 in Keras. Fine-tunes the last layers, applies image augmentation, and evaluates with Precision, Recall, AUC, F1 score, and early stopping for improved performance.

ImranNawar/pneumonia-classifier

Classify Chest X-ray image to pneumonia or normal.

meng-ucalgary/enel-645-project

A project on building deep learning classifier to classify playing cards

ruddanil/NN-MushroomClassification-Py-TensorFlow-SSTU

Implementation of a neural network for solving the problem of mushroom classification based on the TensorFlow library and the pre-trained efficientnet/b0 model.