以图搜图基于Towhee(resnet50 模型) + Milvus
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Updated
Aug 21, 2024 - Python
以图搜图基于Towhee(resnet50 模型) + Milvus
ResNet50 for Image Classification
Open source project for waste detection developed by students of postgraduate course Artificial Intelligence with Deep Learning UPC
Basic recommendation system with mySQL database and API
Deep Learning based Skin Cancer Detection using multiple CNN architectures (VGG, ResNet, DenseNet, EfficientNet, Inception) with image preprocessing using ESRGAN and performance comparison for clinical AI research.
Atreus is an advanced bot designed to play the popular game GTA 5 using cutting-edge computer vision and deep learning techniques. By implementing AlexNet, a deep convolutional neural network, Atreus can interpret game visuals and make strategic decisions in real-time.
cat-dog classifer
we classify the images with keras pre trained models like vgg 16 model ,Resnet-50 model and inception-v3 model
Context Understanding from Videos analyzes video content by extracting frames and audio, then detecting objects, faces, emotions, and actions. It uses Python with OpenCV, MoviePy, and YOLO. Future plans include embedding models for improved context analysis.
💡Utilizing deep learning techniques 🧠 and models such as ResNet50, VGG16, ResNet101, VGG19, DenseNet201, EfficientNetB4, and MobileNetV2 🤖 through transfer learning and fine-tuning 🔧 to improve lung cancer detection from CT scans 🏥.
A breast cancer analysis project using advanced image processing techniques. This research employed CNNs, specifically VGG16, DenseNet121, and ResNet150V2, to analyze histopathological images from the BreakHis dataset on Kaggle, enhancing breast cancer detection and classification.
An AI-driven system that monitors student attentiveness during online lectures using computer vision. It analyzes facial expressions, eye movement, and head pose to provide real-time insights into engagement levels
Brain tumor classification using Deep Learning (ResNet50, PyTorch) on MRI images. Final Year B.Tech AI-ML Project.
A machine learning-based system for detecting and classifying skin diseases through image analysis, utilizing deep learning models and classification pipelines.
Python script leveraging pre-trained ResNet18 for extracting video features from the YouTube Dataset, enabling LSTM-based action recognition models.
Developing a RESTful API using FastAPI to accept an image and return the image type using the ResNet50 (ImageNet) model.
A Large-Scale Dataset for Fish Segmentation and Classification Using Deep Learning Algorithms
A project on building deep learning classifier to classify playing cards
An Automated Material Stream Identification (MSI) system using fundamental Machine Learning (ML) techniques that classifies waste/material images using a classic ML pipeline
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