以图搜图基于Towhee（resnet50 模型） + Milvus

ResNet50 for Image Classification

Basic recommendation system with mySQL database and API

Open source project for waste detection developed by students of postgraduate course Artificial Intelligence with Deep Learning UPC

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

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.

we classify the images with keras pre trained models like vgg 16 model ,Resnet-50 model and inception-v3 model

💡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.

Brain tumor classification using Deep Learning (ResNet50, PyTorch) on MRI images. Final Year B.Tech AI-ML Project.

Vehicle Identify

Developing a RESTful API using FastAPI to accept an image and return the image type using the ResNet50 (ImageNet) model.

Python script leveraging pre-trained ResNet18 for extracting video features from the YouTube Dataset, enabling LSTM-based action recognition models.

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

A Large-Scale Dataset for Fish Segmentation and Classification Using Deep Learning Algorithms

A project on building deep learning classifier to classify playing cards

This project addresses the danger of distracted driving by developing a system that analyzes in-vehicle camera footage. Deep learning models, including self-trained Convolutional Neural Networks (CNNs) and pre-trained architectures like ResNet-50 and VGG-16, are used to identify drivers who are texting, using phones, reaching for objects or talking

Python-based solution for automatic image caption generation using a ResNet-50 CNN and RNN, featuring comprehensive data preprocessing, model training, and evaluation with BLEU score and Cosine Similarity metrics.