Academic Articles & Research Papers

The fluency-based semantic network of LLMs differs from humans

Modern Large Language Models (LLMs) exhibit complexity and granularity similar to humans in the field of natural language processing, challenging the boundaries between humans and machines in language understanding and creativity. However, ...

Target reindexing and residual reconstruction enable reliable retrieval augmented few shot recognition

Abstract Retrieval-augmented few-shot recognition supplements sparsely annotated target classes with external visual samples, but open retrieval results may exhibit unstable quality, semantic mismatch, and cross-domain feature shifts. Direc...

Exploring Scientific Outputs about Globalization: A Conceptual Framework Study

IntroductionBibliometric analysis is widely acknowledged as a robust and systematic approach for examining extensive scholarly literature. It serves as a vital tool for mapping the landscape of contemporary research across various academic ...

DE L’INTERVENTION DES ACTEURS NON ÉTATIQUES POUR LA SCOLARISATION DES ÉLÈVES DÉPLACÉS INTERNES (EDI)

Résumé : La crise sécuritaire à laquelle le Burkina Faso est confronté affecte son système éducatif depuis 2016. Elle est à l’origine de la fermeture de plusieurs milliers d’établissements scolaires et du déplacement des élèves de leurs lie...

An empirical study of LLaMA3 quantization: from LLMs to MLLMs

Abstract The LLaMA family, a collection of foundation language models ranging from 7B to 65B parameters, has become one of the most powerful open-source large language models (LLMs) and the popular LLM backbone of multi-modal large language...

Implementation and Design of a Smart Pharmacy Automation System Using Raspberry Pi

Manual medication dispensing in pharmacies remains prone to human errors and is time-intensive, particularly under high patient loads, while existing commercial automation solutions are cost-prohibitive for small to medium-sized pharmacy se...

AutoWindLoc: Precise Localization of Wind Turbines in High-Resolution Orthophotos for Enhanced Registers

The paper proposes a novel framework for automatically detecting wind turbines in orthophotos, transferring this information to a database, and linking detected turbines to an existing registry to minimize location inaccuracy. This inaccura...

Evaluation of quantization error in computer vision

Due to the important role that digitization error plays in the field of computer vision, a careful analysis of its impact on the computational approaches used in the field is necessary. The authors develop the mathematical tools for the com...

Towards automated metaphase cell detection using foundation models: A SAM and DINO-based approach

Karyotyping is a widely used laboratory technique to detect abnormalities in chromosomes. Karyotyping consists of many steps, including collecting samples, cell culturing and metaphase cell detection. Cytogeneticists examine all the images ...

Deep Learning and Bidirectional Optical Flow Based Viewport Predictions for 360° Video Coding

The rapid development of virtual reality applications continues to urge better compression of 360° videos owing to the large volume of content. These videos are typically converted to 2-D formats using various projection techniques i...

Atrial fibrillation phenotypes derived from multimodal data exhibit distinct electrophysiological substrate characteristics, symptom trajectories, and ablation outcomes.

Effectual pre-processing with quantization error elimination in pose detector with the aid of image-guided progressive graph convolution network (IGP-GCN) for multi-person pose estimation

Multi-person pose estimation (MPE) remains a significant and intricate issue in computer vision. This is considered the human skeleton joint identification issue and resolved by the joint heat map regression network lately. Learning robust ...

The Intelligent Ecosystem: How we are Architecting the Future of Environmental Services with AI

As the global economy confronts the dual imperatives of ecological preservation and technological advancement, we at Veolia, are executing a comprehensive strategy that places Artificial Intelligence (AI) at the core of our operations and f...

The application of deep learning in computer vision

As the deep learning exhibits strong advantages in the feature extraction, it has been widely used in the field of computer vision and among others, and gradually replaced traditional machine learning algorithms. This paper first reviews th...

A Wilson–Cowan reservoir computer for interpretable spatiotemporal vision

Abstract We present a Wilson–Cowan reservoir computer (WC–RC) that treats a retinotopic excitatory–inhibitory neural field as a structured reservoir. Travelling waves and bounded oscillations provide an interpretable spatiotemporal basis, w...

Extraconal Orbital Cavernous Venous Malformations: An Incidental Finding.

Contextually conspicuous species are more likely to be venomous: Habitat-dependent aposematic colouration found throughout snakes.

Automated Detection of Positioning Errors in Bitewing Radiographs Using Deep Learning.

MAT-Fly: An Educational Platform for Simulating Unmanned Aerial Vehicles Aimed to Detect and Track Moving Objects

The main motivation of this work is to propose a simulation approach for a specific task within the Unmanned Aerial Vehicle (UAV) field, i.e., the visual detection and tracking of arbitrary moving objects. In particular, it is described MAT...

Per-Sample Multiple Kernel Approach for Visual Concept Learning

Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL) methods have shown great advantages in visual concept learning. As a visual concep...