A wearable EEG headband detects primary colors from brain activity for color perception.
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Develops new methods to create imperceptible image changes that fool classifiers.
Large language models predict human sensory judgments across multiple modalities.
Computer Vision and machine learning methods were previously used to reveal screen presence of genders in TV and movies. In this work, using head pose, gender detection, and skin color estimation techniques, we demonstrate that the gender disparity in TV in a South Asian country such as Bangladesh exhibits unique chara…
Mechanisms of human color vision are characterized by two phenomenological aspects: the system is nonlinear and adaptive to changing environments. Conventional attempts to derive these features from statistics use separate arguments for each aspect. The few statistical approaches that do consider both phenomena simulta…
Existing model-based reinforcement learning methods often study perception modeling and decision making separately. We introduce joint Perception and Control as Inference (PCI), a general framework to combine perception and control for partially observable environments through Bayesian inference. Based on the fact that…
Study the tradeoff between signal distortion and human perception over finite channels.
A framework isolates VQA reasoning from perception for better model evaluation.
End-to-end autonomous driving perception learns latent features for better performance.
Geometric model explains music perception combining neuroscience and acoustics.
A new loss function for VAEs improves image quality and efficiency.
RETR improves indoor radar perception with a novel transformer model.
Researchers study how teachers' advising relationships influence their perceptions of satisfaction and students, not policy influence.
Existing deep neural networks, say for image classification, have been shown to be vulnerable to adversarial images that can cause a DNN misclassification, without any perceptible change to an image. In this work, we propose shock absorbing robust features such as binarization, e.g., rounding, and group extraction, e.g…
Reconstruction-based learning produces uninformative features for perception tasks.
Perception of artificial agents is one the grand challenges of AI research. Deep Learning and data-driven approaches are successful on constrained problems where perception can be learned using supervision, but do not scale to open-worlds. In such case, for autonomous embodied agents with first-person sensors, percepti…
The paper shows links can be colored with fewer colors than previously thought.
For a link with zero determinants, a Z-coloring is defined as a generalization of Fox coloring. We call a link having a diagram which admits a non-trivial Z-coloring a Z-colorable link. The minimal coloring number of a Z-colorable link is the minimal number of colors for non-trivial Z-colorings on diagrams of the link.…
PeL separates sensory interface optimization from decision learning.
Study on knots using 17 colors, finding specific color assignments.
It was shown that any -colorable link has a diagram which admits a non-trivial -coloring with at most four colors. In this paper, we consider minimal numbers of colors for non-trivial -colorings on minimal diagrams of -colorable links. We show, for any positive integer $N…
PERCEPT detects changes in high-dimensional data streams using topological data analysis.
Sensorimotor contingency theory offers a promising account of the nature of perception, a topic rarely addressed in the robotics community. We propose a developmental framework to address the problem of the autonomous acquisition of sensorimotor contingencies by a naive robot. While exploring the world, the robot inter…
Aicardi's invariant is extended to colored singular links using graphical calculus.
While perception tasks such as visual object recognition and text understanding play an important role in human intelligence, the subsequent tasks that involve inference, reasoning and planning require an even higher level of intelligence. The past few years have seen major advances in many perception tasks using deep …
The paper finds minimum Dehn colors for knots and defines useful graphs for coloring.
Default-ERM shortcut learning persists even without additional information.
DGP learns speech recognition by modeling complex relationships between utterances.
The study improves deep learning models for safer autonomous vehicles.
We determine the minimal number of colors for non-trivial -colorings on the standard minimal diagrams of -colorable torus links. Also included are complete classifications of such -colorings and of such -colorings by only four colors, which are shown by using rack colorin…
Motivated by vision-based control of autonomous vehicles, we consider the problem of controlling a known linear dynamical system for which partial state information, such as vehicle position, is extracted from complex and nonlinear data, such as a camera image. Our approach is to use a learned perception map that predi…
K. Ichihara and E. Matsudo introduced the notions of -colorable links and the minimal coloring number for -colorable links, which is one of invariants for links. They proved that the lower bound of minimal coloring number of a non-splittable -colorable link is 4. In this paper, we sh…
Factor complexity for a vertex coloring of a regular tree is the number of colored -balls up to color-preserving automorphisms. Sturmian colorings are colorings of minimal unbounded factor complexity . In this article, we prove an induction algorithm for Sturmian colorings using colored ba…
We prove that any -colorable knot is presented by an -colored diagram where exactly five colors of eleven are assigned to the arcs. The number five is the minimum for all non-trivially -colored diagrams of the knot. We also prove a similar result for any -colorable ribbon -knot.
This survey article discusses three aspects of knot colorings. Fox colorings are assignments of labels to arcs, Dehn colorings are assignments of labels to regions, and Alexander-Briggs colorings assign labels to vertices. The labels are found among the integers modulo n. The choice of n depends upon the knot. Each typ…
The study characterizes torus links' coloring quivers using dihedral quandles.
For each odd prime p, and for each non-split link admitting non-trivial p-colorings, we prove that the maximum number of Fox colors is p. We also prove that we can assemble a non-trivial p-coloring with any number of colors, from the minimum to the maximum number of colors. Furthermore, for any rational link, we prove …
Paper describes a state sum formula for a graph coloring polynomial.
The minimal coloring number of a -colorable link is the minimal number of colors for non-trivial -colorings on diagrams of the link. In this paper, we show that the minimal coloring number of any non-splittable -colorable links is four. As an example, we consider the link obtained by…
We analyse perception and memory, using mathematical models for knowledge graphs and tensors, to gain insights into the corresponding functionalities of the human mind. Our discussion is based on the concept of propositional sentences consisting of \textit{subject-predicate-object} (SPO) triples for expressing elementa…
An algorithm detects anomalies based on human perception principles.
New coding theorem shows achievable rate matches theoretical limit.
For any link and for any modulus we introduce an equivalence relation on the set of non-trivial m-colorings of the link (an m-coloring has values in Z/mZ). Given a diagram of the link, the equivalence class of a non-trivial m-coloring is formed by each assignment of colors to the arcs of the diagram that is obtaine…
Introduced coloring-allowed invariants of planar knotoids with the coloring number.
Study of quandle coloring quivers with dihedral quandles.
In this article we present the following new fact for prime p=11. For knots 6_2 and 7_2, mincol_{11} 6_2 = 5 = mincol_{11} 7_2, along with the following feature. There is a pair of diagrams, one for 6_2 and the other one for 7_2, each of them admitting only non-trivial 11-colorings using 5 colors, but neither of them a…
Convolutional networks outperform shallow classifiers on certain tasks due to hierarchical structure.
Method transfers feature representation from large to small models using perception coherence.