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traffic-analysis

This project does traffic analysis on videos by using vision and deep learning techniques

traffic-signs-tensorflow

Traffic Signs Detection and Recognition with Tensorflow

transana

Cross-platform software for Qualitative Analysis of video, audio, still image, and text data

tremorfreeme

TremorFreeMe's support application to control device and synchronize data

tutorials_stock_prediction

two-cell-hco

A two-cell half-center oscillator made for ECE4580/7580 (Computational Neuroscience) at the University of Missouri.

ucsf-data_driven_neuro

A repository to store course materials for the data-driven neuroscience in python short-course.

udacimak

Udacity Nanodegree and Course Downloader

udacity-comput3rvision

The repository conatins projects done during CVND .

unr_psy_763

Notebooks for seminar in computational cognitive neuroscience

unsupervised-features-learning-for-image-classification

Recently, image classification draw attentions of many researchers. The need of object recognition grows drastically, especially in the context of biometric, biomedical imaging and real time scene understanding. Computer vision task is the most challenging in machine learning. For that reason, it's fundamental to tackle this concern using appropriate clustering and classification techniques. However, the quest for the best unsupervised features extraction remain an open problem even if CNNs reach a remarkable success, establishing new state-of-the-art. In this context, we study from an acute insight standpoint the standard clustering models K-means, GMM and Naive Bayes classification algorithm in order to draw conclusion and underline their limits for such complicated tasks. To what extent are k-means and GMM efficient ? Why they fail and how to circumvent their weaknesses.

utah_bmi_sig

Some notebooks on Machine Learning and Natural Language Processing from the University of Utah Biomedical Informatics (BMI) Special Interest Group (SIG)

vehicle-detection

Created vehicle detection pipeline with two approaches: (1) deep neural networks (YOLO framework) and (2) support vector machines ( OpenCV + HOG).

video-analysis

Video analysis for blurring, face detection and clustering.

video-analysis-for-surveillance

Analyzing CCTV videos to find interesting events

video-analysis-workshop

video-boundingbox-labeler

A labeling tool aimed at data prepartion for YOLO deep learning

video-frame-pie

convert video file to image frame, for analysis

video-pose-extractor

Dockerfile and instructions for human pose estimation implementation using Caffe, OpenCV 3.1.0 and Python 2.7.

watson-wbme

IBM Watson Visual Recognition project for the 9th Workshop on Biomedical Engineering (skin lesions classification)

webvalley2017

Companion Ipython notebook for the lecture "Machine learning for the working (biomedical) researcher" @Webvalley2017

whosthere

arduino/rpi project

wifi_camera_smart_robot_car

This library is developed by arducam and is applicable to WIFI camera smart robot car

wsn_iot

WSN APPLICATION FOR MONITORING PATIENT’S BODY TEMPERATURE IN HOSPITALS

xcorr-notebooks

An ongoing collection of ipython notebooks on neuroscience from xcorr: computational neuroscience.

xmlutils.py

Python scripts for processing XML documents and converting to SQL, CSV, and JSON [UNMAINTAINED]

yolo-dna

yolo-image-detection

yolo_object_detection

This is the code for "YOLO Object Detection" by Siraj Raval on Youtube

yolotf