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Found 16 papers, 0 papers with code
FolkTalent: Enhancing Classification and Tagging of Indian Folk Paintings
Indian folk paintings have a rich mosaic of symbols, colors, textures, and stories making them an invaluable repository of cultural legacy.
AnoGAN for Tabular Data: A Novel Approach to Anomaly Detection
Anomaly detection, a critical facet in data analysis, involves identifying patterns that deviate from expected behavior.
Approximate Nullspace Augmented Finetuning for Robust Vision Transformers
In this work, we provide a finetuning approach to enhance the robustness of vision transformers inspired by the concept of nullspace from linear algebra.
X-lifecycle Learning for Cloud Incident Management using LLMs
to generate insights for detection, root causing and mitigating of incidents.
A bi-objective $ε$-constrained framework for quality-cost optimization in language model ensembles
We propose an ensembling framework that uses diverse open-sourced Large Language Models (LLMs) to achieve high response quality while maintaining cost efficiency.
Understanding EEG signals for subject-wise Definition of Armoni Activities
The learning is performed in a closed-loop by using feedback in the form of change in affective state.
Machine Learning Framework: Competitive Intelligence and Key Drivers Identification of Market Share Trends Among Healthcare Facilities
A reliable framework which helps identify factors impacting a Healthcare Provider Facility or a Hospital (from here on termed as Facility) Market Share is of key importance.
On Deep Neural Network Calibration by Regularization and its Impact on Refinement
We find that many calibration approaches with the likes of label smoothing, mixup etc.
RandCrowns: A Quantitative Metric for Imprecisely Labeled Tree Crown Delineation
Tree crown delineation provides key information from remote sensing images for forestry, ecology, and management.
Exploring Target Driven Image Classification
We argue that, for any arbitrary category $\mathit{\tilde{y}}$, the composed question 'Is this image of an object category $\mathit{\tilde{y}}$' serves as a viable approach for image classification via.
Assessing The Importance Of Colours For CNNs In Object Recognition
In this paper, we empirically investigate the importance of colours in object recognition for CNNs.
Single- and narrow-line photoluminescence in a boron nitride-supported MoSe$_2$/graphene heterostructure
Since this exciton has a picosecond radiative lifetime at low temperature, comparable with the energy transfer time, its low-temperature photoluminescence is only quenched by a factor of $3. 3 \pm 1$ and $4. 4 \pm 1$ in the presence of mono- and bilayer graphene, respectively.
Mesoscale and Nanoscale Physics Materials Science
Machine learning predicts early onset of fever from continuous physiological data of critically ill patients
This study aims to develop novel algorithms that can accurately predict fever onset in critically ill patients by applying machine learning technique on continuous physiological data.
Optimization of Ensemble Supervised Learning Algorithms for Increased Sensitivity, Specificity, and AUC of Population-Based Colorectal Cancer Screenings
Stool DNA tests, the modern benchmark for CRC screening, have a much higher sensitivity and specificity, but also cost \$600, take two weeks to process, and are not for high-risk individuals or people with a history of polyps.
Learning to Hash-tag Videos with Tag2Vec
In this paper, we study the problem of generating relevant and useful hash-tags for short video clips.
From Traditional to Modern : Domain Adaptation for Action Classification in Short Social Video Clips
In this paper, we focus on the problem of unsupervised action classification in wild vines using traditional labeled datasets.
