Autonomous car, Communication, image processing
Cooperation Autonomous driving is an extremely difficult task requiring absolute reliability under a great variety of situations. Currently, it is almost impossible for a single sensor to handle the complexity due to limited perspective and intrinsic weakness such as...
Deep Learning, image processing
Sensors Various types of sensors are used for perception in the self-driving industry. Most current solutions rely on either a camera or LIDAR as the main sensor. A camera captures reflections of light passively and stores data as 2D images. In contrast, LIDAR...
Computer, Deep Learning, image processing
Jag är en pythonprogrammerare. Jag har fyra års erfarenhet av python. Jag är redo att acceptera Python-projektet. Keras, TensorFlow, Scipy, Numpy, Konstgjort neuralt nätverk i Python, Bildbehandling i Python, OpenCV, Pybrain, Matplotlib, Scikit-Learn , Pandas...
Deep Learning, image processing
An autoencoder is an unsupervised algorithm for generating efficient encodings. The input layer and the target output is typically the same. The layers between decrease and increase in the following fashion: The bottleneck layer is the middle layer with a reduced...
Deep Learning, image processing
Approximate nearest neighbour oh yeah (ANNOY) is a method for faster nearest neighbour search. ANNOY builds trees by random projections. The tree structure makes it easier to find the closest matches. You can create an ANNOYIndex for faster retrieval as shown here:...
Deep Learning, image processing
The retrieval can be slow because it’s a brute-force method. Matching can be made faster using approximate nearest neighbor. The curse of dimensionality also kicks in, as shown in the following figure: With every increasing dimension, complexity increases as the...
Deep Learning, image processing
NumPy’s linalg.norm is useful for computing the Euclidean distance. The similarity between the query image and target database can be computed between the images by calculating the Euclidean distances between the features as shown here: dist =...
Deep Learning, image processing
The sequence of steps to get the best matches from target images for a query image is called the retrieval pipeline. The retrieval pipeline has multiple steps or components. The features of the image database have to be extracted offline and stored in a database. For...
Deep Learning, image processing
The technique of Content-based Image Retrieval (CBIR) takes a query image as the input and ranks images from a database of target images, producing the output. CBIR is an image to image search engine with a specific goal. A database of target images is required for...
Computer, image processing, MATLAB, MATLAB code
function [yi, ypi] = sincdint(x, y, xi, c) % SINCDINT 1-D piecewise discrete sinc interpolation % SINCDINT(X,Y,XI,C) interpolates to find YI, the values of the % underlying function Y at the points in the array XI, using % piecewise discrete sinc interpolation. X and...
Computer, image processing
This section details the use of the Fire-i program to control the NAVITAR scope for capturing images and movies to use with the line tracking program or for imaging purposes. 1. Connect the Firewire cable to the NAVITAR scope. 2. Open Fire-i . 3. Ensure the settings...
Computer, data mining, database of image, image processing, Medicine
Accelerating Parallel Image Reconstruction Using Random Projection Prologue Random projection has been used for data dimension reduction . The concept of random projection is related to compressed sensing , a topic that has attracted many attentions recently. By...
Computer, data mining, database of image, image processing, Medicine
Compressed Sensing MRI Parallel imaging has led to revolutionary progress in the field of rapid MRI in the past two decades. However, as discussed in the previous section, the maximum acceleration that can be achieved in parallel imaging is limited by the number and...
Computer, data mining, database of image, image processing, Medicine
The Need for Speed in MRI MR imaging speed is of critical importance in many clinical applications. However, the imaging speed with which gradient-encoded MR images can be acquired is fundamentally limited by the sequential nature of gradient-based MR acquisitions, in...
Computer, data mining, database of image, image processing, Medicine
MR Image Reconstruction As shown in Eq. (2.11), MR signal from a two-dimensional plane is a spatial integration of the spin density against the sinusoidal spatial modulation generated by encoding gradients. In other words, the MR signal comprises projections of the...
Computer, data mining, database of image, image processing, Medicine
MRI Signal NMR Phenomenon The physical phenomenon behind MRI is nuclear magnetic resonance (NMR), which was first discovered in the 1940s. An atomic nucleus with an odd number of protons possesses an angular momentum J called spin, which generates a tiny magnetic...
Computer, data mining, database of image, image processing, Medicine
Magnetic Resonance Imaging Magnetic Resonance Imaging (MRI) is a non-invasive and powerful imaging modality, with a broad range of applications in both clinical diagnosis and basic scientific research. Comparing to other medical imaging modalities, MRI does not use...
Computer, data mining, database of image, image processing
Principal Component Analysis Principal component analysis (PCA) is a dimensionality reduction technique that attempts to recast a dataset in a manner that nds correlations in data that may not be evident in their native basis and creates a set of basis vectors in...
Computer, data mining, database of image, image processing, Medicine
Practical Considerations in Computational Sensing Computational sensing as a eld is continuing to grow at a rapid pace. The number of journal publications related to computational sensing has steadily increased every year since 2008 . There is now a major Optical...
Computer, data mining, database of image, image processing
Compressive Sensing Traditionally, in order to increase the resolution of a sensor, one had to increase the number of measurements. This means that the SWAP-C must also increase. A camera with just a few megapixels FPA costs less than one with hundreds of megapixels....
Computer, data mining, database of image, image processing, Medicine
Indirect Imaging While Golay, Fennimore, and others were leveraging multiplexing to eliminate trade offs in traditional sensors, an entirely disparate group of researchers were working on imaging techniques for which there was no isomorphic analog. In these cases the...
Computer, data mining, database of image, image processing
Development of Multiplexing in Sensing Multiplexing in sensing is the idea that each measurement sample is a physical combination of various parts of the analog signal-of-interest. Multiplexing is a powerful tool that can be exploited by the sensor designer to...
Computer, data mining, database of image, image processing
Isomorphic Sensing In Greek, the word isomorphic loosely translates to \equal in form.” Traditional sensors perform isomorphic sensing. In the context of this dissertation, an isomorphic sensor is any sensor which attempts to produces measurement data that...
Computer, data mining, database of image, image processing, Medicine
Efficient Cell Segmentation and Tracking of Developing Plant Meristem Introduction Proper understanding of the causal relationship between cell growth patterns and gene expression dynamics is one of the major topics of interest in developmental biology. Information...
image processing
The world is made of three dimensions (3-D). Humans perceive the world in 3-D but really see 2-D images in the eye retina. We have the aptitude to estimate the depth of objects in a scene. We want to mimic this aptitude of recovering 3-D perception of a scene from a...
image processing
Discussion We faced some issues in the hardware design while building the circuit for TIS G2. Initially we had used a 3.6V battery to power the LT1932 chip and 74AC14 chip at the same time. However, when we constructed the circuit on the breadboard and tested it, we...
image processing
In this section, some tests were designed to compare the capabilities of TIS G1 and TIS G2 in characterizing an inclusion embedded in the soft tissue. The models are developed using spherical targets and PVC tissue phantom with base, depth, and intermediate layers....
image processing
Here is a list of the material we need to build second generation tactile imaging sensor. The frame of LED was made by glue (Arrow). First we used the glue gun to melt the glue stick and put glue around the LED tubes, and then used paper to shape the glue. For other...
image processing
Introduction In the literature, the existing tactile imaging sensor system (TIS G1) has proven to be successful in capturing tactile images and measuring mechanical properties (Lee and Won, 2011). However, the dimensions of PDMS in TIS are 2.3cm × 2.0cm × 1.2cm, which...
image processing
Tactile Imaging System Tactile Sensing Human have five senses: smell, taste, sight, hearing and touch. The touch sense is also called tactile sensation. It is recognized by the receptors of touch which are found mainly in the skin. Since Hippocrates, the human sense...
image processing
Motivation The most common cancer among women in Western countries is breast cancer (Parkin et al 2002). Worldwide, breast cancer accounts for 22.9% of all cancers in women. According to the information from the American Cancer Society, breast cancer caused 458,503...
image processing
Object Location and Tracking In Image Processing Dividing and organizing an image in the desired way and detecting and isolating the edges of desired objects are the key components in recognizing and then tracking the objects. There are countless algorithms already in...
image processing
Edge Detection In Image Processing Locating the boundaries of desired objects is another fundamental aspect of image processing. Helping to further segment images in order to locate and match objects, edge detection works by determining the gradient. This involves...
image processing
Image Processing Image analysis is performed using a variety of algorithms and methods. Some techniques are more effective than others and usually depend on the particular application. These algorithms can be classified many ways into various logical groups which can...
data mining, image processing, Medicine
Introduction Radiation therapy utilizes ionizing radiation with the goal of curing or palliating disease and minimizing damage to healthy tissue. Localization using Image Guided Radiation Therapy (IGRT) is performed in order to ensure tumor location and minimize...
data mining, image processing, Medicine
standardized uptake values (SUV) Positron emission tomography (PET) has become a widely utilized functional imaging modality. The combination of x-ray computed tomography (CT) with PET gives both structural and functional information from a single two part scan as...
image processing
History and relevance of footwear impressions The discipline of forensic comparative science comprises the examination of multiple forms of evidence, most notably, latent prints, track impressions (footwear and tire), firearms and questioned documents. Track...
image processing
Bilaterally located on either side of the nose, the human eye(s), also referred to as the globe(s), is a vital organ necessary in visual processing. The human globe is spherical in nature and is somewhat flattened in the anteroposterior area . Each globe resides...
image processing
At this time, little to no research has been conducted on the use of postmortem iris scanning as a biometric measurement of identification. Similar to deoxyribonucleic acid (DNA), irises are a highly individualizing components of the human body and are unique between...
image processing
Lexicon Since our approach is based mainly on lexical cues, we need a lexicon of word pairs, which is used during the alignment rocess. The lexicon can be prepared manually within CSV or XLS file and updated with new word pairs as necessary. owever, n order to...
