Review of MIT’s WHY! Conceptual Contributions It is an interesting and challenging question to resolve how we determine the “why” behind an image. It is posited that it is a result of “Theory of the Mind” and psychophysics researchers hypothesize that our capacity to reliably infer another person’s motivation stems from our…

Review of DeViSE — Conceptual Contributions In DeViSE, the authors tackle the issue that visual recognition systems are often limited in their ability to scale to large numbers of classification categories in part due to difficulty in acquiring such a balanced dataset as well as the traditionally rigid nature of classification within defined classes. The authors…

Review of this article Conceptual Contributions This paper aims to improve image captioning, which is one of the primary challenges in the intersection of CV and NLP. Tangible process improves applications from aiding visually impaired users to human computer interaction. …

Overview of From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions — Semantic interpretation, or making inferences on the meaning of atext is a fundamental step in language understanding. Drawing from our human ability to envisionmental images when prompted by a description, this paper introduces a novel approach for automaticallydenoting similarities between descriptions of everyday situations via sets of images and captions…

An Overview of Segmenting Scenes by Matching Image Composites Introduction One of the major goals in computer vision is semantic object segmentation, which is essentially identifying different objects that have semantic meaning (toothbrush or tree) within an image. …

An Overview of Spherical CNNs, Best Paper Award in the 2018 ICLR Conference by Taco Cohen and his team! — Convolutional Neural Networks (CNNs), which is a class of deep learning neural networks, have become the go-to method for 2D image detection/classification as it produce accurate results without taking too much computing power or time. You can find out more about how it works here and the original motivation, which…

Review of Microsoft’s Deep Residual Learning for Image Recognition — Note: This paper was a bit difficult for me and I relied heavily on other sources to help me understand the material. …

A Review of Joseph Halpern’s A Modification of the Halpern-Pearl Definition of Causality Waves: An Introduction Just as the waves ebb and flow, the principles of causality, cause and effect push and pull the world around us into the way that it is. Despite the fact that causality in principle is something that…

Finding a Balance Using First Order Logic and Markov Random Fields — There is a huge need in computer science, specifically in developing technologies of artificial intelligence and machine learning for representing knowledge as well as making predictions on the world/for future. There are two primary approaches to solving this problem: There is the logical mindset where we approach this problem through…