Research
On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

Trend · papers per month

7142128 · Jun 202019922001200920172026
48 results for color perception

A wearable EEG headband detects primary colors from brain activity for color perception.

problem Detecting primary colors from brain activity for color perception.
method Spectral power features, statistical features, and correlation features from continuous Morlet wavelet transform; dimensionality reduction techniques like Forward Feature Selection and Stacked Autoencoders; Random Forest Classifier.
result Best overall accuracy of 80.6% for intra-subject classification.

Develops new methods to create imperceptible image changes that fool classifiers.

problem Improving the robustness of image classifiers by creating subtle changes undetectable to humans.
method Two methods: Edge-Aware and Color-Aware, designed to reduce detectability of image perturbations.
result Demonstrated that the new methods effectively cause misclassification and are computationally efficient.

Large language models predict human sensory judgments across multiple modalities.

problem Determining the extent of perceptual information in language.
method State-of-the-art large language models were used to predict sensory judgments across six psychophysical datasets.
result Large language models can predict human sensory judgments across multiple modalities with significant correlation to human data.

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…

2017-11-14abs ↗pdf ↗

Study the tradeoff between signal distortion and human perception over finite channels.

problem Characterize the distortion-perception tradeoff for finite channels with arbitrary metrics.
method Solve linear programming problems to compute the distortion-perception function and optimal reconstructions.
result DP function is piecewise linear in the perception index.

End-to-end autonomous driving perception learns latent features for better performance.

problem Current autonomous driving systems are complex and require human engineering.
method Sequential latent representation learning for end-to-end perception.
result End-to-end perception model solves detection, tracking, localization, and mapping problems.

Geometric model explains music perception combining neuroscience and acoustics.

problem Rationalize and predict psycho-acoustic phenomena in music perception.
method Combining neuroscientific theories with acoustic observations, a geometric model of the space of all chords is created.
result The geometric model allows for rigorous studies of psychoacoustic quantities like roughness and harmonicity.

A new loss function for VAEs improves image quality and efficiency.

problem Training VAEs to generate realistic images requires a loss function that reflects human perception.
method Based on Watson's perceptual model, the loss function computes a weighted distance in frequency space, accounts for luminance and contrast masking, and is extended to color images.
result VAEs trained with the new loss function generated high-quality, less blurry images with fewer artifacts and less computational resources.

RETR improves indoor radar perception with a novel transformer model.

problem Indoor radar perception lacks models tailored for multi-view radar settings.
method RETR extends DETR architecture with depth-prioritized feature similarity, tri-plane loss, and radar-to-camera transformation.
result RETR outperforms state-of-the-art methods by 15.38+ AP for object detection and 11.91+ IoU for instance segmentation.

Researchers study how teachers' advising relationships influence their perceptions of satisfaction and students, not policy influence.

problem Understanding the relationship between teachers' advising relationships and their perceptions of satisfaction and students.
method Proposed a novel joint model of network and item responses (JNIRM) with correlated latent variables.
result Teachers' advising relationships contribute more to satisfaction and students than to influence over educational policies.

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…

2019-05-26abs ↗pdf ↗

Reconstruction-based learning produces uninformative features for perception tasks.

problem Misalignment between reconstruction-based learning and perception tasks.
method Investigated the impact of input space reconstruction on feature learning for perception tasks.
result Reconstruction-based learning allocates model capacity to a subspace with 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…

2020-02-13abs ↗pdf ↗

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.…

2016-05-26abs ↗pdf ↗

PeL separates sensory interface optimization from decision learning.

problem Optimizing sensory interfaces without task-specific information.
method Formal separation of perception and decision learning, using metrics for stability, informativeness, and geometry.
result Updates preserving invariants are orthogonal to decision gradients.

PERCEPT detects changes in high-dimensional data streams using topological data analysis.

problem Detecting changes in high-dimensional data streams, especially when embedded in a low-dimensional space.
method Leverages topological data analysis to learn embedded topology as a point cloud via persistence diagrams, then applies non-parametric monitoring for detecting changes.
result Demonstrates efficient detection of online changes from high-dimensional data streams.

Aicardi's invariant F(L)F(L) is extended to colored singular links using graphical calculus.

problem Constructing an invariant for colored classical and singular links.
method State-sum model using graphical calculus for oriented, colored, 4-valent planar graphs.
result Extends F(L)F(L) to colored singular links, showing it's stronger than HOMFLY-PT polynomial.

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 …

2016-08-24abs ↗pdf ↗

The paper finds minimum Dehn colors for knots and defines useful graphs for coloring.

problem Finding the minimum number of colors for Dehn colorings of knots.
method Analyzes Dehn colorings for knots and defines R\R-palette graphs.
result For Dehn pp-colorable knots, the minimum number of colors is at least log2pfloor+2\lfloor \log_2 p floor +2.

DGP learns speech recognition by modeling complex relationships between utterances.

problem Modeling complex relationships in speech recognition without relational data.
method Bayesian nonparametric deep learning method (DGP) that generates infinite probabilistic graphs.
result DGP successfully infers relationships among utterances without relational data during training.

We determine the minimal number of colors for non-trivial Z\mathbb{Z}-colorings on the standard minimal diagrams of Z\mathbb{Z}-colorable torus links. Also included are complete classifications of such Z\mathbb{Z}-colorings and of such Z\mathbb{Z}-colorings by only four colors, which are shown by using rack colorin…

2019-08-02abs ↗pdf ↗

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…

2019-07-08abs ↗pdf ↗

Factor complexity bφ(n)b_φ(n) for a vertex coloring φφ of a regular tree is the number of colored nn-balls up to color-preserving automorphisms. Sturmian colorings are colorings of minimal unbounded factor complexity bφ(n)=n+2b_φ(n) = n+2. In this article, we prove an induction algorithm for Sturmian colorings using colored ba…

2016-09-20abs ↗pdf ↗

We prove that any 1111-colorable knot is presented by an 1111-colored diagram where exactly five colors of eleven are assigned to the arcs. The number five is the minimum for all non-trivially 1111-colored diagrams of the knot. We also prove a similar result for any 1111-colorable ribbon 22-knot.

2015-05-12abs ↗pdf ↗

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…

2013-01-23abs ↗pdf ↗

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 …

2012-05-07abs ↗pdf ↗

The minimal coloring number of a Z\mathbb{Z}-colorable link is the minimal number of colors for non-trivial Z\mathbb{Z}-colorings on diagrams of the link. In this paper, we show that the minimal coloring number of any non-splittable Z\mathbb{Z}-colorable links is four. As an example, we consider the link obtained by…

2017-05-22abs ↗pdf ↗

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…

2020-01-29abs ↗pdf ↗

An algorithm detects anomalies based on human perception principles.

problem Anomaly detection in data.
method Inspired by Gestalt psychology and Helmholtz principle, the algorithm models anomalies as unexpected elements in random distributions.
result The algorithm efficiently detects anomalies with minimal user intervention and promising results on multivariate data.

For any link and for any modulus mm 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…

2012-08-05abs ↗pdf ↗

Study of quandle coloring quivers with dihedral quandles.

problem Link invariants and their enhancements using quandles.
method Introduced shadow quandle coloring quivers and cocycle quivers, studied equivalence with quandle coloring numbers and shadow quandle cocycle invariants.
result Equivalence of quandle coloring quivers with quandle coloring numbers and shadow quandle cocycle quivers with shadow quandle cocycle invariants for specific 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…

2013-08-28abs ↗pdf ↗

Convolutional networks outperform shallow classifiers on certain tasks due to hierarchical structure.

problem Understanding why convolutional networks outperform shallow classifiers on specific tasks.
method Approximation theory, visual tasks with deterministic scrambling, and network performance evaluation.
result Hierarchical structure is crucial for convolutional networks' performance on certain tasks, but not all.

Method transfers feature representation from large to small models using perception coherence.

problem Transfer feature representation from large to small models.
method Defines perception coherence, proposes loss function to minimize.
result Method outperforms or achieves on-par performance compared to strong baseline methods.