Computer vision for pattern detection in chromosome contact maps

Exponential Maps for Computer Vision

In computer vision, the exponential map is the natural generalisation of the ordinary exponential function to matrix elements. The technique is based on generating a manifold embedding of the geometric features of the scene on which to estimate trajectories primarily of motion or invariance. An advantage of using the exponential map is the existence of a closed form time-update equation for the...

metrics for the detection of changed buildings in 3d old vector maps using als data (case study: isfahan city)

هدف از این تحقیق، ارزیابی و بهبود متریک های موجود جهت تایید صحت نقشه های قدیمی سه بعدی برداری با استفاده از ابر نقطه حاصل از لیزر اسکن جدید شهر اصفهان می باشد . بنابراین ابر نقطه حاصل از لیزر اسکنر با چگالی حدودا سه نقطه در هر متر مربع جهت شناسایی عوارض تغییر کرده در نقشه های قدیمی سه بعدی استفاده شده است. تمرکز ما در این تحقیق بر روی ساختمان به عنوان یکی از اصلی ترین عارضه های شهری می باشد. من...

Statistical model of intra-chromosome contact maps

The statistical properties of intra-chromosome maps obtained by a genome-wide chromosome conformation capture method (Hi-C) are described in the framework of the hierarchical crumpling model of heteropolymer chain with quenched disorder in the primary sequence. We conjecture that the observed Hi-C maps are statistical averages over many different ways of hierarchical genome folding, and show th...

Advances in Computer Vision and Pattern Recognition

Drowsiness Detection for Drivers Using Computer Vision

Drowsiness detection system is regarded as an effective tool to reduce the number of road accidents. This project proposes a non-intrusive approach for detecting drowsiness in drivers, using Computer Vision. The algorithm is coded on OpenCV platform in Linux environment. The parameters considered to detect drowsiness are face and eye detection, blinking, eye closure and gaze. Input is captured ...