Sevim Cengiz,Ph.D.'s starred repositories
AI-For-Beginners
12 Weeks, 24 Lessons, AI for All!
From-0-to-Research-Scientist-resources-guide
Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.
LLM-Agent-Paper-List
The paper list of the 86-page paper "The Rise and Potential of Large Language Model Based Agents: A Survey" by Zhiheng Xi et al.
python_for_microscopists
https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1
LSTM-Human-Activity-Recognition
Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
CoreML-Models
Converted CoreML Model Zoo.
pytorch-frame
Tabular Deep Learning Library for PyTorch
Human-Activity-Recognition-using-CNN
Convolutional Neural Network for Human Activity Recognition in Tensorflow
recommendation
Recommendation System using ML and DL
RWF2000-Video-Database-for-Violence-Detection
A large scale video database for violence detection, which has 2,000 video clips containing violent or non-violent behaviours.
SwiftCSVExport
Swift CSV Export is rich features framework and it helpful to read and write CSV in simple way.
adult-human-brain
Cytograph version used for adult human-brain analysis
Sensor-Based-Human-Activity-Recognition-DeepConvLSTM-Pytorch
DeepConvLSTM model for sensor-based human activity recognition in Pytorch
Vision_Audio_and_Multimodal_Projects
This repository includes all computer vision, audio, document AI, and multimodal projects.
LSTMEnsemble4HAR
sourcecode for IMWUT 2017 paper "Ensembles of Deep LSTM Learners for Activity Recognition using Wearables" (Guan, Ploetz)
Sensor-Based-Human-Activity-Recognition-LSTMsEnsemble-Pytorch
Ensembles of Deep LSTM Learners for Human Activity Recognition using Wearables in Pytorch
MotionTracking
The Application uses CoreMotion and LocationManager to collect the data and saves it to a file that is transferred to the iPhone using WatchConnectivity