arXiv subjects

Wei Ding

Publications and source records attributed to Wei Ding.

77 records · Page 5Linked to original sources

arXiv2016

Crater Detection via Convolutional Neural Networks

Craters are among the most studied geomorphic features in the Solar System because they yield important information about the past and present geological processes and provide information about the relative ages of observed geologic formations. We present a method for automatic crater detection using advanced machine learning to deal with the large amount of satellite imagery collected. The challenge of automatically detecting craters comes from their is complex surface because their shape erodes over time to blend into the surface. Bandeira provided a seminal dataset that embodied this challenge that is still an unsolved pattern recognition problem to this day. There has been work to solve this challenge based on extracting shape and contrast features and then applying classification models on those features. The limiting factor in this existing work is the use of hand crafted filters on the image such as Gabor or Sobel filters or Haar features. These hand crafted methods rely on domain knowledge to construct. We would like to learn the optimal filters and features based on training examples. In order to dynamically learn filters and features we look to Convolutional Neural Networks (CNNs) which have shown their dominance in computer vision. The power of CNNs is that they can learn image filters which generate features for high accuracy classification.

cs.CV↗

arXiv2015

The cost of reading research. A study of Computer Science publication venues

What does the cost of academic publishing look like to the common researcher today? Our goal is to convey the current state of academic publishing, specifically in regards to the field of computer science and provide analysis and data to be used as a basis for future studies. We will focus on author and reader costs as they are the primary points of interaction within the publishing world. In this work, we restrict our focus to only computer science in order to make the data collection more feasible (the authors are computer scientists) and hope future work can analyze and collect data across all academic fields.

cs.DL↗

arXiv2015

A Common-Factor Approach for Multivariate Data Cleaning with an Application to Mars Phoenix Mission Data

Data quality is fundamentally important to ensure the reliability of data for stakeholders to make decisions. In real world applications, such as scientific exploration of extreme environments, it is unrealistic to require raw data collected to be perfect. As data miners, when it is infeasible to physically know the why and the how in order to clean up the data, we propose to seek the intrinsic structure of the signal to identify the common factors of multivariate data. Using our new data driven learning method, the common-factor data cleaning approach, we address an interdisciplinary challenge on multivariate data cleaning when complex external impacts appear to interfere with multiple data measurements. Existing data analyses typically process one signal measurement at a time without considering the associations among all signals. We analyze all signal measurements simultaneously to find the hidden common factors that drive all measurements to vary together, but not as a result of the true data measurements. We use common factors to reduce the variations in the data without changing the base mean level of the data to avoid altering the physical meaning.

cs.AI↗

arXiv2013

Large-scale MU-MIMO: It Is Necessary to Deploy Extra Antennas at Base Station

In this paper, the large-scale MU-MIMO system is considered where a base station (BS) with extremely large number of antennas (N) serves relatively less number of users (K). In order to achieve largest sum rate, it is proven that the amount of users must be limited such that the number of antennas at the BS is preponderant over that of the antennas at all the users. In other words, the antennas at the BS should be excess. The extra antennas at the BS are no longer just an optional approach to enhance the system performance but the prerequisite to the largest sum rate. Based on this factor, for a fixed N, the optimal K that maximizes the sum rate is further obtained. Additionally, it is also pointed out that the sum rate can be substantially improved by only adding a few antennas at the BS when the system is N=KM with M denoting the antennas at each user. The derivations are under the assumption of N and M going to infinity, and being implemented on different precoders. Numerical simulations verify the tightness and accuracy of our asymptotic results even for small N and M.

cs.IT↗

arXiv1999

Multimodal Surrogates for Video Browsing

Three types of video surrogates - visual (keyframes), verbal (keywords/phrases), and combination of the two - were designed and studied in a qualitative investigation of user cognitive processes. The results favor the combined surrogates in which verbal information and images reinforce each other, lead to better comprehension, and may actually require less processing time. The results also highlight image features users found most helpful. These findings will inform the interface design and video representation for video retrieval and browsing.

cs.DL↗