Many of us take our vision for granted, but rarely do we measure how well we can see. In this study, the authors investigate the ability of people of different ages to read progressively fainter letters in dark light. They find that the ability to see in dim light drops drastically after age 30. The ability to read fainter letters worsens after age 30 as well. These findings should help inform lighting decisions everywhere from restaurants to road signs.

In this study the authors develop an app for faster chess game entry method to help chess learners improve their game. This culminated in the Augmented Reality Chess Analyzer (ARChessAnalyzer) which uses traditional image and vision techniques for chess board recognition and Convolutional Neural Networks (CNN) for chess piece recognition.

Plant diseases can cause up to 50% crop yield loss for the popular tomato plant. A mobile device-based method to identify diseases from photos of symptomatic leaves via computer vision can be more effective due to its convenience and accessibility. To enable a practical mobile solution, a “shallow” convolutional neural networks (CNNs) with few layers, and thus low computational requirement but with high accuracy similar to the deep CNNs is needed. In this work, we explored if such a model was possible.

Modern artificial neural networks have been remarkably successful in various applications, from speech recognition to computer vision. However, it remains less clear whether they can implement abstract concepts, which are essential to generalization and understanding. To address this problem, the authors investigated the above vs. below task, a simple concept-based task that honeybees can solve, using a conventional neural network. They found that networks achieved 100% test accuracy when a visual target was presented below a black bar, however only 50% test accuracy when a visual target was presented below a reference shape.

The authors looked at the dynamics of tennis serves from professional and amateur athletes.

Natural selection shapes the evolution of all organisms, and one question of interest is whether natural selection will reach a "stopping point": a stable, ideal, value for any particular trait. Madhan and Kanagavel tackle this question by building a computer simulation of trait evolution in organisms.

Here the authors investigated the optical possibilities of gelatin and acrylic in regards to potential implementations at soft contact lenses. They fabricated lenses of different shapes and evaluated the refraction of laser light finding that gelatin needed to be thickened or increased in curvature to account for its lower refractive index compared to plastics, or used in a mixture to strengthen the lens.

Semantic segmentation - labelling each pixel in an image to a specific class- models require large amounts of manually labeled and collected data to train.

Here, beginning from an initial interest in the possibility to use a computer to automatically solve a geometry diagram parser, the authors developed their own Fast Geometry Diagram Parser (FastGDP) that uses clustering and corner information. They compared their own methods to a more widely available, method, GeoSolver, finding their own to be an order of magnitude faster in most cases that they considered.

In this study, the authors investigate whether phototaxis and odortaxis in Drosophila melanogaster occurs through linear summation of cues including light and attractive odorants.